The AI job market moves fast. We keep up so you don't have to.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous electrical engineering problems reflecting professional practice.Evaluate AI solutions for correctness, assumptions, and constraints.Validate calculations or simulations using Python (NumPy, Pandas, SciPy).Improve AI reasoning to align with industry-standard logic.Apply structured scoring criteria to multi-step problems. What we look for This opportunity is a good fit for electrical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Electrical Engineering or related fields, e.g. Electronics, Microelectronics, Embedded Systems, Power Systems, etc. 3+ years of professional electrical engineering experience Strong written English (C1/C2) • Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PE, CEng, EUR ING, RPEQ) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $40/hour*  Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

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🚀 About WRITERWRITER is where the world's leading enterprises orchestrate AI-powered work. Our vision is to expand human capacity through superintelligence. And we're proving it's possible – through powerful, trustworthy AI that unites IT and business teams together to unlock enterprise-wide transformation. With WRITER's end-to-end platform, hundreds of companies like Mars, Marriott, Uber, and Vanguard are building and deploying AI agents that are grounded in their company's data and fueled by WRITER's enterprise-grade LLMs. Valued at $1.9B and backed by industry-leading investors including Premji Invest, Radical Ventures, and ICONIQ Growth, WRITER is rapidly cementing its position as the leader in enterprise generative AI.Founded in 2020 with office hubs in San Francisco, New York City, Austin, Chicago, and London, our team thinks big and moves fast, and we're looking for smart, hardworking builders and scalers to join us on our journey to create a better future of work with AI.📐 About the roleEvery company grows differently, and at WRITER, our growth is directly tied to empowering our users to create better content, faster, and at an unprecedented scale. As a strategic solutions architect, you'll be at the forefront of this mission, working directly with our largest and most strategic prospects to identify, validate, and build innovative generative AI solutions that unlock massive business value. This isn't just about selling a product; it's about deeply understanding complex enterprise needs and architecting a future where AI transforms how our customers operate. You'll be instrumental in shaping how the world's leading companies adopt and scale AI, making a tangible impact on both their success and WRITER’s continued leadership in the enterprise generative AI space.This is a full-time, hybrid role based out of our San Francisco hub. You will report directly to the VP of solutions architecture.🦸🏻‍♀️ What you'll doDrive strategic technical discovery with Fortune 500 prospects and customers, translating complex business challenges into clear, impactful technical solutions for AI-powered workArchitect and design robust, scalable, and secure generative AI solutions for enterprise clients, leveraging WRITER's platform, APIs, and custom applications to solve critical business problemsLead the development and execution of compelling proofs of concept (PoCs) and demonstrations, building custom templates and integrating WRITER's capabilities to showcase transformative value and accelerate time-to-value for customersServe as a trusted technical advisor to C-suite executives, VPs of Engineering, and AI leaders, guiding their generative AI strategy and collaborating to define enterprise-level architecture roadmapsPartner closely with WRITER's Product and Engineering teams, providing critical feedback from customer engagements to influence our product roadmap and ensure our solutions meet evolving market needsChampion the adoption of WRITER's platform and APIs, educating prospects and partners on the art of the possible with generative AI and empowering them to build their own innovative solutions.⭐️ What you need5+ years of experience in technical customer-facing roles such as solutions architect, enterprise architect, or sales engineering, ideally within a high-growth, B2B SaaS company serving Fortune 500 clientsDeep expertise in generative AI principles, large language models (LLMs), and prompt engineering best practices, with a passion for staying ahead of the curve in this rapidly evolving fieldProficiency in Python for building out WRITER Framework solutions and extensive experience with APIs, microservices, and cloud AI platforms (e.g., Azure AI, AWS SageMaker) to integrate AI capabilities into complex enterprise systemsExceptional communication and presentation skills, able to simplify complex technical concepts into clear, compelling business language for diverse audiences, from technical teams to executive leadershipA highly versatile and tenured problem solver, capable of leading multi-stakeholder discovery sessions, uncovering root causes, and architecting innovative solutions to complex business and technical challengesA builder's mindset and a proven ability to Connect deeply with customer needs, Challenge the status quo with innovative AI solutions, and Own the technical success and impact of client engagements 🍩 Benefits & perks (US Full-time employees)Generous PTO, plus company holidaysMedical, dental, and vision coverage for you and your familyPaid parental leave for all parents (12 weeks)Fertility and family planning supportEarly-detection cancer testing through GalleriFlexible spending account and dependent FSA optionsHealth savings account for eligible plans with company contributionAnnual work-life stipends for:Wellness stipend for gym, massage/chiropractor, personal training, etc.Learning and development stipendCompany-wide off-sites and team off-sitesCompetitive compensation, company stock options and 401kWRITER is an equal-opportunity employer and is committed to diversity. We don't make hiring or employment decisions based on race, color, religion, creed, gender, national origin, age, disability, veteran status, marital status, pregnancy, sex, gender expression or identity, sexual orientation, citizenship, or any other basis protected by applicable local, state or federal law. Under the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.By submitting your application on the application page, you acknowledge and agree to WRITER's Global Candidate Privacy Notice.

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About ElevenLabsElevenLabs is an AI research and product company transforming how we interact with technology.We launched in January 2023 with the first human-like AI voice model. Today, we serve millions of users and thousands of businesses - from fast-growing startups to large enterprises like Deutsche Telekom and Meta. Our investors are some of the world's most prominent, including Andreessen Horowitz, ICONIQ Growth and Sequoia. We've raised $781M in funding and our last valuation was $11B - multiples of 11, always. We have expanded from voice into three main platforms:ElevenAgents enables businesses to deliver seamless and intelligent customer experiences, with the integrations, testing, monitoring, and reliability necessary to deploy voice and chat agents at scale.ElevenCreative empowers creators and marketers to generate and edit speech, music, image, and video across 70+ languages.ElevenAPI gives developers access to our leading AI audio foundational models.Everything we do is the result of the creativity and commitment of our team - builders doing the best work of their lives. We are researchers, engineers, and operators. IOI medalists and ex-founders. If you want to work hard and create lasting positive impact, we want to hear from you.How we workHigh-velocity: Rapid experimentation, lean autonomous teams, and minimal bureaucracy.Impact not job titles: We don’t have job titles. Instead, it’s about the impact you have. No task is above or beneath you.AI first: We use AI to move faster with higher-quality results. We do this across the whole company—from engineering to growth to operations.Excellence everywhere: Everything we do should match the quality of our AI models.Global team: We prioritize your talent, not your location.What we offerInnovative culture: You’ll be part of a generational opportunity to define the trajectory of AI, surrounded by a team pushing the boundaries of what’s possible.Growth paths: Joining ElevenLabs means joining a dynamic team with countless opportunities to drive impact - beyond your immediate role and responsibilities.Learning & development: ElevenLabs proactively supports professional development through an annual discretionary stipend.Social travel: We also provide an annual discretionary stipend to meet up with colleagues each year, however you choose.Annual company offsite: Each year, we bring the entire team together in a new location - past offsites have included Croatia and Italy.Co-working: If you’re not located near one of our main hubs, we offer a monthly co-working stipend.About the roleAs a Forward Deployed Engineer Strategist, you'll work as part of a driven and creative team of Engineers, Product Designers, and other Strategists to deploy our voice AI technology against the most challenging problems our customers face. Your mission is to synthesize disconnected streams of thought into a cohesive understanding of what the most important problem is, what the data means, what the product needs, what users are motivated by, and where the impact could be.No two days are the same, but as a FDE Strategist you can expect to:Meet with strategic customers to understand their critical audio and voice AI needs and locate their biggest pain points.Identify relevant use cases through deep engagement with customer problems and workflows, and work with Engineers to implement our voice and audio AI technology into innovative solutions.Design and architect bespoke integrations for customers, ensuring our technology fits seamlessly into their products and operations.Guide customers on best practices for implementing our voice and audio AI models to maximize their effectiveness.Present the results of our work and proposals for future work to audiences ranging from technical teams to C-suite executives.Collaborate with our Research and Product teams to incorporate field insights into ElevenLabs' software products and AI models.Build and deliver compelling demos of our voice and audio AI technology to new and existing customers.Scope out potential applications in new industries and expand our AI solutions across different sectors globally.Take full ownership of end-to-end execution of major projects for our most strategic partners, working hands-on to deliver high-impact solutions.Collaborate daily with our customers' engineering and executive teams to ensure optimal implementation of ElevenLabs' technologies.RequirementsExperience working with customers in a technical capacity. It's ok if you only worked with customers in student clubs or side projects, as long as you are interested in working closely with them.Basic proficiency in Python and understanding of API integration to implement scripts and help with prototyping/demo building.Excellent communication and problem-solving skills, especially in terms of ability to summarize complex technical concepts and using logic in pursuing optimal solutions.A proven track record of taking ownership of complex projects and delivering results.Adaptability to work across different customer environments and technical use cases.Technical aptitude to quickly understand our voice and audio AI models and their applications.LocationThis role is remote and can be executed globally. If you prefer, you can work from our offices in Bangalore, Dublin, London, New York, San Francisco, Tokyo, and Warsaw.#LI-Remote

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About Snorkel At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data. We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes between 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!About Snorkel We’re on a mission to democratize AI by building the definitive AI data development platform. The AI landscape has gone through incredible change between 2016, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler! As an Applied AI Engineer, you’ll research and utilize state-of-the-art Gen AI and machine learning (ML) techniques to successfully deliver solutions to our customers. You will work directly with our customers to understand their business and technical needs and design and deliver AI solutions to solve them - either by leveraging Snorkel Flow or developing custom approaches when needed. You will also help define Snorkel’s Applied AI tooling by translating repeatable real-world challenges into reusable solution recipes, workflows, best practices, and platform-level capabilities that become part of Snorkel Flow’s next generation of AI tooling. We move fast and are constantly prototyping and innovating new ways to deliver value to our customers. This position is ideal for someone who enjoys solving complex problems, bridging the gap between AI technology and business value, working directly with customers, keeping up-to date with AI research, and standardizing bespoke solutions into internal recipes and staying naturally curious about the infrastructure that underpin the Applied AI stack end-to-end. Main Responsibilities Partner with customers to build and deploy impactful Gen AI and machine learning solutions, from use case scoping and data exploration to model development and deployment. This may involve leveraging Snorkel Flow or designing custom approaches using state-of-the-art tools, with the goal of delivering real business value and informing the evolution of the Snorkel platform. Develop and implement state of the art AI systems such as retrieval-augmented generation (RAG), fine-tuning pipelines, prompt engineering recipes and agentic workflows. Create augmented real-world datasets and comprehensive evaluation workflows to ensure model reliability, transparency, and stakeholder trust. A data- and evaluation-first mindset is essential for success in this role. Forge and manage relationships with our customers’ leadership and stakeholders to ensure successful development and deployment of AI projects with Snorkel Flow. Collaborate closely with pre-sales Solutions and Product teams to map customer needs to existing capabilities, prioritize roadmap gaps, and guide successful project setup. Work with other Applied AI Engineers to standardize solutions and contribute to internal tooling and best practices. Lead stakeholder education on quantitative capabilities, helping them to understand the strengths and weaknesses of different approaches and what problems are best-suited for Snorkel AI. Serve as the voice of our customers for new AI paradigms, data science workflows, and share customer feedback to product teams. Conduct one-to-few and one-to-many enablement workshops to transfer knowledge to customers considering or already using Snorkel AI. Annual travel up to 25%. Preferred Qualifications B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience. 3+ years of customer-facing experience in the design and implementation of AI/ML solutions. Proficiency in Python, including strong grounding in software engineering fundamentals (e.g., modular design, testing, profiling, packaging) and experience with modern Python constructs and libraries for type validation and typed data modeling (e.g., pydantic), building type-safe systems (e.g., mypy), testing (e.g., pytest), packaging and environment configuration (e.g., poetry), API and service frameworks (e.g., FastAPI), serialization and structured data handling (e.g., msgspec), and orchestration tooling relevant to ML deployment (e.g., Ray, Airflow). Expertise across the Applied AI stack, spanning classical ML libraries (e.g., scikit-learn), deep learning frameworks (e.g., PyTorch), foundation-model ecosystems (e.g., Hugging Face Transformers), vector/embedding tooling (e.g., FAISS), data processing frameworks (e.g., pandas, Spark), retrieval/RAG tooling (e.g., Chroma, Weaviate), synthetic dataset curation, evaluation workflows, and LLM orchestration, workflow, agent authoring tools (e.g., LlamaIndex, LangGraph, CrewAI). Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement. Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos. Ability to work in a fast-paced environment and balance priorities across multiple projects at once. Compensation range for Tier 1 locations of San Francisco Bay Area $172K - $300K OTE. All offers also include equity in the form of employee stock options. Our compensation ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Locations Redwood City, CA - Hybrid; San Francisco, CA - Hybrid - US; New York, NY - Hybrid #LI-CG1Salary Range $172,000—$300,000 USDBe Your Best at Snorkel Joining Snorkel AI means becoming part of a company that has market proven solutions, robust funding, and is scaling rapidly—offering a unique combination of stability and the excitement of high growth. As a member of our team, you’ll have meaningful opportunities to shape priorities and initiatives, influence key strategic decisions, and directly impact our ongoing success. Whether you’re looking to deepen your technical expertise, explore leadership opportunities, or learn new skills across multiple functions, you’re fully supported in building your career in an environment designed for growth, learning, and shared success. Snorkel AI is proud to be an Equal Employment Opportunity employer and is committed to building a team that represents a variety of backgrounds, perspectives, and skills. Snorkel AI embraces diversity and provides equal employment opportunities to all employees and applicants for employment. Snorkel AI prohibits discrimination and harassment of any type on the basis of race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local law. All employment is decided on the basis of qualifications, performance, merit, and business need. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation.

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About Arize AI is rapidly transforming the world. As generative AI reshapes industries, teams need powerful ways to monitor, troubleshoot, and optimize their AI systems. That’s where we come in. Arize AI is the leading AI & Agent Engineering observability and evaluation platform, empowering AI engineers to ship high-performing, reliable agents and applications. From first prototype to production scale, Arize AX unifies build, test, and run in a single workspace—so teams can ship faster with confidence. We’re a Series C company backed by top-tier investors, with over $135M in funding and a rapidly growing customer base of 150+ leading enterprises and Fortune 500 companies. Customers like Booking.com, Uber, Siemens, and PepsiCo leverage Arize to deliver AI that works.Note: The nature of this role requires candidates to be based in the Buenos Aires area, though there isn't an in-office requirement. The Opportunity We’re looking for an Application Engineer who thrives on solving hard problems with code. In this role, you'll have the opportunity to work at the cutting edge of generative AI in a high-impact role with autonomy and ownership. What You’ll Do Debug and fix issues in our platform (and ship PRs with your fixes). Build internal tools and copilots powered by generative AI to supercharge our team. Rapidly prototype proof-of-concepts for customer use cases. Work across Engineering, Product, and Solutions to unblock customers and push the boundaries of AI adoption. What We’re Looking For You have 2-5 years of experience in software. Strong in Python and Golang; comfortable shipping fixes in production systems. Hands-on with generative AI (LLM APIs, frameworks, building copilots or automations) Hands-on with OpenTelimetry and deep familiarity with distributed tracing concepts. Familiarity with AI frameworks (CrewAI, Langchain, Langgraph, DiFy, LiteLLM, etc). Familiarity or eagerness to learn JavaScript/TypeScript. Great debugger, creative problem solver, and fast learner. Independent and resourceful. You create solutions, not dependencies. Bonus Points (but not required!) Experience in a customer-facing role Built copilots, plugins, or custom GenAI-powered applications. Open-sourced or contributed PRs to real codebases. Startup or fast-moving environment experience. Actual compensation is determined based upon a variety of job related factors that may include: transferable work experience, skill sets, and qualifications. Total compensation also includes unlimited paid time off, generous parental leave plan, and others for mental and wellness support.More About Arize Arize’s mission is to make the world’s AI work—and work for people. Our founders came together through a shared frustration: while investments in AI are growing rapidly across every industry, organizations face a critical challenge—understanding whether AI is performing and how to improve it at scale. Learn more about what we're doing here: https://techcrunch.com/2025/02/20/arize-ai-hopes-it-has-first-mover-advantage-in-ai-observability/ https://arize.com/blog/arize-ai-raises-70m-series-c-to-build-the-gold-standard-for-ai-evaluation-observability/ Diversity & Inclusion @ Arize Our company's mission is to make AI work and make AI work for the people, we hope to make an impact in bias industry-wide and that's a big motivator for people who work here. We actively hope that individuals contribute to a good culture Regularly have chats with industry experts, researchers, and ethicists across the ecosystem to advance the use of responsible AI Culturally conscious events such as LGBTQ trivia during pride month We have an active Lady Arizers subgroup

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $46 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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Please submit your CV in English and indicate your level of English proficiency.Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves You’ll create challenging coding test cases that push AI coding systems to their limits: Review and refine realistic coding tasks based on provided production codebases with realistic scope, requirements and information sources  Write comprehensive functional tests that validate actual end-to-end behavior and edge-cases, not just superficial checksCraft “fair but hard” challenges where the AI has all the context it needs, but has to work for it (information scattered across files and external sources, complex reasoning required) Analyze AI failures to understand what the model struggles with vs. what it masters Iterate based on feedback from expert QA reviewers who score your work on 7 quality criteriaWhat we look forThis opportunity is a good fit for experienced developers, software engineers, and/or test automation specialists open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Computer Science, Software Engineering or related fields 5+ years in software development, primarily Python (pytest, async/await, subprocess, file operations) Background in Full-Stack development, with an equal focus on building React-based interfaces and robust Back-end systemsExperience writing tests (functional, integration – not just running them) Docker containers (running evaluations locally in containers) CI/CD understanding (GitHub Actions as a user: triggers, labels, reading results) English proficiency - B2How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paid Effort estimate Tasks for this project are estimated to take 20 hours to complete, depending on complexity. This is an estimate and not a schedule requirement; you choose when and how to work. Tasks must be submitted by the deadline and meet the listed acceptance criteria to be accepted.CompensationOn this project, contributors can earn up to $45 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous statistics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for statisticians with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Statistics or related fields, e.g. Probability Theory, Mathematical Statistics, Applied Statistics, etc. 3+ years of professional mathematics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PStat, CAP, SAS Certifications) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $34 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $34 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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About the RoleWe’re hiring a Go-To-Market Engineer to build the internal systems that power how Magical identifies demand, engages buying groups, accelerates deals, and scales revenue.This is not a sales role — and it’s not a traditional engineering role.This role sits at the intersection of engineering, automation, AI, and revenue operations. You’ll design and ship the signal infrastructure, agent workflows, and orchestration tooling that turns messy GTM data into precise, automated action: from account intelligence and buying-stage detection to SDR alerts, personalization, and deal acceleration.If you love building fast, automating everything, and seeing immediate business impact, you’ll thrive here. What You’ll DoBuild GTM Signal Infrastructure - Design automated systems that score ICP fit, map buying committees, support visibility into buying group engagement and coverage, and track multi-threaded engagement across target accounts.Capture Intent & Engagement at Scale - Aggregate and normalize intent, website, content, ad, and event signals to understand real buying behavior by account and persona.Detect Buying Stage & Deal Health - Translate multi-signal engagement patterns into buying-stage readiness, momentum shifts, and stalled-deal risk indicators.Orchestrate Automated GTM Actions - Trigger real-time outreach, personalization, audience syncing, nurtures, and deal-acceleration plays based on live engagement signals.Build Internal Tooling & Agent Workflows - Ship AI agents, integrations, and automation tooling that turn manual GTM workflows into scalable revenue systems.Partner With Marketing, Sales, and RevOps - Translate GTM strategy into scalable systems and automation.Add Data Quality & Governance - Maintain data reliability, normalization, and signal accuracy across GTM systems What “AI Native” Means HereWe’re looking for someone who is fluent in using AI to build. You should be comfortable:Automating data enrichment & research workflowsGenerating structured account intelligence from unstructured sourcesDetecting anomalies or pipeline risk patternsSummarizing engagement insights for GTM teamsPrompting effectively and building repeatable prompt workflowsUsing tools like Claude Code, Codex, Cursor, or similar to build fasterBuilding multi-step agent flows and orchestrationsWorking with RAG-style architectures (without needing to be an embeddings researcher)Designing tool-calling agents that interact with APIs and internal systems What We’re Looking ForNew grad or early-career engineer who has shipped real production code (internships, co-ops, side projects all count)Alternatively, a marketer with strong technical skills who uses automation and AI to engineer scalable, signal-driven growth systemsIn either case, you should have a strong scripting and automation comfort level (Python and/or TypeScript preferred)Experience working with APIs, data pipelines, and integration-heavy systemsBuilder mindset: you see a problem, you fix it, you ship itHigh ownership, high urgency, low egoProduct instincts: you can think through user needs and design workflows that make senseInterest in GTM and how companies actually scale revenue Nice to HaveExperience with browser automation tools (Playwright, Puppeteer, Selenium)Experience building internal dashboards, admin tools, or automation frameworksExperience building agent workflows or multi-agent systemsExperience with SaaS GTM (ABM, lifecycle marketing, sales pipelines, onboarding, implementation, CS workflows) This Role is NOT a Fit If…You need highly detailed specs before you can startYou prefer long planning cycles over shipping and iteratingYou like research projects more than building real systems used dailyYou want a slow-paced environment with heavy structure and oversight What Success Looks LikeWithin your first 90 days, you will have shipped systems that:automate GTM signal capture and orchestrationsurface high-intent accounts earlierimprove SDR efficiency and deal velocityreduce manual ops work across revenue teamscreate durable automation leverage across GTMincrease signal reliability and GTM decision confidence Month One ExpectationWithin your first month, you’ll likely become the number 1 user of Magical’s own product, building and iterating with it daily while also creating tooling around it. Why Join MagicalWork directly on problems tied to revenue and real-world adoptionShip constantly and see impact immediatelyOperate like a founder: high trust, high ownership, high velocityBuild the tooling layer that scales an AI company

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level automotive engineering problems grounded in real practice; Evaluate AI-generated solutions for correctness, assumptions, and engineering logic; Validate analytical or numerical results using Python (NumPy, SciPy, Pandas); Improve AI reasoning to align with first principles and accepted engineering standards; Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for automotive engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Automotive Engineering or related fields, e.g. Mechatronics, Manufacturing Engineering, Mechanical Engineering, Aerospace Engineering, etc. 3+ years of professional automotive engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation is project-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design rigorous physics problems reflecting professional practice; Evaluate AI solutions for correctness, assumptions, and constraints; Validate calculations or simulations using Python (NumPy, Pandas, SciPy); Improve AI reasoning to align with industry-standard logic; Apply structured scoring criteria to multi-step problems.What we look for This opportunity is a good fit for physicists with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Physics or related fields, e.g. Engineering Physics, Thermodynamics, Statistical Mechanics, Optics and Acoustics, etc. 3+ years of professional physics experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., CPhys, EurPhys, MInstP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.

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About the RoleYou will architect, build, and scale the internal technology ecosystem that accelerates workforce productivity, eliminates operational friction, and gives the company a compounding infrastructure advantage. You will treat internal tools with the same product rigour and user-centricity as any external product — because the quality of internal systems directly determines organisational velocity.You will lead a cross-functional engineering team, make high-stakes build-vs-buy decisions, and drive AI adoption into internal workflows. This role requires someone who can see the company’s operational architecture as a system design problem and solve it with software.What You Will DoInternal Platform Strategy & RoadmapOwn the end-to-end strategy and roadmap for all internal tools, platforms, and automation — treating internal technology as a product, not a cost centre.Make strategic build-vs-buy decisions, knowing when a custom-built solution creates a lasting advantage and when a SaaS tool is the right answer.Map current and next-state process flows across the entire internal toolchain and lead systems transformation for internal teams.Systems Architecture & EngineeringArchitect and maintain the full engineering lifecycle for internal platforms — from ideation and design through deployment, iteration, and deprecation.Build seamless, API-first ecosystems that integrate internal tools across HR systems, finance platforms, knowledge management, CRM, and developer infrastructure.Own system reliability and operational resilience: establish success metrics for uptime, performance, and employee productivity.Design scalable, secure architectures using cloud-native principles, microservices, and modern integration patterns.AI & AutomationLead the strategy for integrating AI and LLMs into internal workflows — reimagining how knowledge is shared, decisions are supported, and work is executed across the organisation.Deploy intelligent automation tools — including AI where appropriate — to streamline internal processes and improve decision-making.Evaluate and integrate AI-assisted troubleshooting, proactive recommendations, and intelligent automation into the internal platform layer.Stay ahead of technology trends and drive continuous experimentation — you build prototypes, not slide decks.Developer Experience & ProductivityReduce cognitive load for internal users by providing golden paths, standardised workflows, and self-service capabilities.Ensure frictionless onboarding and seamless integration across the tool ecosystem.Measure platform success through adoption rates, user satisfaction, DORA metrics, and productivity impact — not feature count.Team LeadershipBuild, lead, and mentor a high-performing team of engineers and engineering managers.Cultivate a collaborative engineering culture rooted in ownership, speed, and craftsmanship.Provide technical mentorship and create growth paths for individual contributors and managers alike.Foster psychological safety and a feedback-driven environment that empowers people to do their best work.Cross-Functional CollaborationPartner with People, Finance, Engineering, Legal, and Operations leadership to translate complex business needs into a unified technical vision.Serve as the bridge between business stakeholders and the engineering team — you speak both languages fluently.Align internal platform investments with broader company strategy and demonstrate measurable ROI.What You Will NeedMust-Have12+ years of experience in software engineering, with at least 5 years in engineering leadership (managing teams or managing managers).Strong hands-on technical background: you’ve built production systems and can still credibly review architecture, code, and system design.Deep understanding of cloud-based systems (AWS, GCP, or Azure), APIs, microservices, data pipelines, and modern infrastructure.Proven track record of building and scaling internal tools or platforms that serve cross-functional business teams — not just engineering.Experience making build-vs-buy decisions and managing a portfolio of custom-built and third-party tools.Strong experience designing and building internal platforms and automation systemsStrong product thinking: you define success in terms of user outcomes and business impact, not technical output.Experience navigating the full SDLC from ideation through deprecation — you know when to build, iterate, and retire.Excellent communication skills: you can articulate complex technical concepts to non-technical executives and translate business problems into engineering roadmaps.Nice-to-HaveExperience at a high-growth technology or AI-native company that scaled rapidly.Background in platform engineering, developer experience, or internal developer platforms (IDPs).Familiarity with HRIS, ERP, and business systems integration (Workday, Salesforce, NetSuite, etc.).Experience with cybersecurity best practices and compliance frameworks for internal systems.Prior experience leading internal technology through M&A integrations or multi-entity consolidation.Exposure to knowledge management systems, internal search, and enterprise AI assistants.Experience integrating AI/LLMs into internal workflows or productivity toolsWhat Success Looks LikeWithin 30 days: Completed a full audit of the existing internal toolchain, identified the top friction points, and presented a prioritised roadmap.Within 60 days: Shipped at least two high-impact internal tools or automations that measurably improve productivity, and established team operating rhythm.Within 12 months: The internal tools ecosystem is a recognised competitive advantage — teams actively request new capabilities, AI is embedded in daily workflows, and internal NPS is consistently high.Who You AreAn engineer who thinks like a CEO. You’ve built production systems, led engineering teams, and understand that the best internal tools don’t just save time — they change how an organisation thinks and moves. You’re obsessed with removing friction, allergic to manual workarounds, and energised by the idea that great internal infrastructure compounds into organisational speed. You believe internal tools deserve the same craft as customer-facing products. You see AI not as a buzzword but as the most important lever for internal productivity in a generation, and you want to be the person who pulls it.How We WorkWe operate as a small, senior, hands-on team. Engineers own features end-to-end — from design discussion through production monitoring.Code reviews and design reviews are expected for all meaningful changes. We discuss architecture openly, make decisions quickly, and ship frequently.Interview processIf there appears to be a fit, we'll reach out to schedule 3, but no more than 4 interviews.Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, the process to offer may be shorter.

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SUPERHUMAN MAIL 👉 We exist so that professionals end each day feeling happier, more productive, and closer to achieving their potential. Our customers get through their inboxes twice as fast; many see inbox zero for the first time in years. Today we are… The fastest email experience in the world Loved and adored: see what our customers say 📣 We've joined forces with Grammarly to build the AI-native productivity suite of the future, with Superhuman as the central communication layer. This partnership accelerates our mission to help professionals achieve their potential — now at even greater scale. Come shape the future of email, communication, and productivity! BUILD LOVE 💜 At Superhuman, we deeply understand how to build products that people love. We incorporate fun and play; we infuse magic and joy; we make experiences that amaze and delight. It all starts with the right team — a team that deeply cares about values, customers, and each other. CREATE MASSIVE IMPACT 🚀 We're not solving a small problem, and we're not addressing a small market. We're going after email; the one activity that consumes more of our work day than any other. Our ambition doesn't stop there. Next: calendars, notes, contacts, and team communication. We are building the productivity platform of the future. DO THE BEST WORK OF YOUR LIFE 🌟 We have created the frameworks for how to build product market fit and redefined the narrative of how to onboard customers successfully. We have shown the world it’s possible to build a premium productivity brand. Our investors included Andreessen Horowitz, First Round Capital, IVP, Tiger Global Management, Sam Altman, and the founders of Gmail, Dropbox, Reddit, Discord, Stripe, GitHub, AngelList, and Intercom. This time, we’re swinging beyond the fences and fundamentally rethinking how individuals and teams should collaborate. We are building a household brand and a worldwide organization. We are here to do the best work of our lives, and we hope you are too. ROLE 👩🏽‍💻👨‍💻 Own the observability and lifecycle management of AI features across the organization Build tools and infrastructure to enable teams to develop, monitor, and optimize LLM-powered features Design and implement closed-loop evaluation pipelines that automatically validate prompt changes Develop comprehensive metrics and dashboards to track LLM usage: cost per feature, token patterns, and latency. Create systems that tie user feedback to specific prompts and LLM calls Establish best practices and processes for the full lifecycle of prompts: development, testing, deployment, and monitoring Collaborate with engineering teams across the org to ensure they have the tools and visibility needed to build high-quality AI features Technologies we use: Go, Postgres, Kubernetes, Google Cloud, various LLM providers (OpenAI, Anthropic, Google Vertex) SOUND LIKE YOU? 🙌 Experience: You have 4+ years of software development experience with a focus on backend engineering, DevOps, ML Ops, or SRE work. You're proficient in at least one back-end programming language (ideally Go). You have hands-on experience with observability, metrics, and monitoring systems. AI Enthusiast: You believe AI will revolutionize how we work as well as the experiences that we create for our customers. Driven by passion and curiosity, you leverage AI to dramatically increase your own productivity and the impact of your team. Metrics-Driven: You understand percentiles (P90, P95), know how to build meaningful dashboards, and can turn raw data into actionable insights. You've worked with monitoring and observability tools. Systems Thinker: You think in terms of pipelines, lifecycles, and closed loops. You know how to build scalable infrastructure that enables other teams to move faster. Remarkable Quality: You produce work that is striking, worthy of attention, and a contribution to the state of the art. Asynchronous Communicator: You’re effective across various mediums (especially Slack, Notion, and email) and can produce and consume detailed written materials as needed without sacrificing speed. You respond quickly and thoughtfully to unblock others and speed things up. Start-to-Finish Ownership: Acts with 100% responsibility for their own outcomes as well as the outcomes of the company. Bias to action: Speed matters. Takes rapid and decisive steps forward, even in the face of uncertainty, recognizing action is the catalyst for progress and growth. Growth Mindset: You embrace challenges, welcome feedback, and believe you and others can always grow. SALARY INFO 💸 Superhuman takes a market-based approach to compensation, which means base pay may vary depending on your location. Base pay may vary considerably depending on job-related knowledge, skills, and experience. The expected salary ranges for this position are outlined below by location and may be modified in the future. Canada: $128,000-$174,000 CAD Mexico: $1,928,000-$2,405,000 MXN Brazil: R$562,000-R$702,000 BRL Argentina: $103,000-$128,000 USD The salary ranges do not reflect total compensation, which includes base salary, benefits, and company equity. This range is intentionally broad because we are open to considering candidates at multiple levels of seniority within engineering. The exact salary offered will depend on the candidate’s skills, experience, and the level at which they join our team. BENEFITS 🎁 Superhuman offers all team members competitive pay along with a benefits package encompassing the following and more: Excellent health care (including a wide range of medical, dental, vision, mental health, and fertility benefits) Disability and life insurance options 401(k) and RRSP matching (US & Canada only) Paid parental leave 20 days of paid time off per year, 12 days of paid holidays per year (17 days for LatAm), two floating holidays per year, and flexible sick time Generous stipends (including those for caregiving, pet care, wellness, your home office, and more) Annual professional development budget and opportunities Superhuman takes a market-based approach to compensation, so base pay may vary by location. COME JOIN US 🎟️ We value our differences, and we encourage all to apply — especially those whose identities are traditionally underrepresented in tech organizations. We do not discriminate on the basis of race, religion, color, gender expression or identity, sexual orientation, ancestry, national origin, citizenship, age, marital status, veteran status, disability status, political belief, or any other characteristic protected by law. Superhuman is an equal opportunity employer and a participant in the US federal E-Verify program (US). We also abide by the Employment Equity Act (Canada). #LI-Remote

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $55 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $32 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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This opportunity is only for candidates currently residing in the specified country. Your location may affect eligibility and rates. Please submit your resume in English and indicate your level of English proficiency.At Mindrift, innovation meets opportunity. We believe in using the power of collective intelligence to ethically shape the future of AI.What we doThe Mindrift platform connects specialists with AI projects from major tech innovators. Our mission is to unlock the potential of Generative AI by tapping into real-world expertise from across the globe.About the RoleGenAI models are improving very quickly, and one of our goals is to make them capable of addressing specialized questions and achieving complex reasoning skills. If you join the platform as a Data Science AI Trainer, you’ll have the opportunity to collaborate on these projects.  Although every project is unique, you might typically: Design original computational data science problems that simulate real-world analytical workflows across industries (telecom, finance, government, e-commerce, healthcare).Create problems requiring Python programming to solve (using pandas, numpy, scipy, sklearn, statsmodels, matplotlib, seaborn).Ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks).Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction.Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility.Base problems on real business challenges: customer analytics, risk assessment, fraud detection, forecasting, optimization, and operational efficiency.Design end-to-end problems spanning the complete data science pipeline (data ingestion → cleaning → EDA → modeling → validation → deployment considerations).Incorporate big data processing scenarios requiring scalable computational approaches.Verify solutions using Python with standard data science libraries and statistical methods.Document problem statements clearly with realistic business contexts and provide verified correct answers. CompensationOn this project, contributors can earn up to $15 per hour equivalent, depending on their level and pace of contribution.Compensation varies across projects depending on scope, complexity, and required expertise. Please note that other projects on the platform may offer different earning levels based on their requirements.How to get started Simply apply to this post, qualify, and get the chance to contribute to projects aligned with your skills, on your own schedule. From creating training prompts to refining model responses, you’ll help shape the future of AI while ensuring technology benefits everyone.RequirementsYou hold a Master’s or PhD Degree in Data Science, Statistics, Mathematics, Computer Science, or related quantitative field. You have at least 5 years of hands-on data science experience with proven business impact.You have portfolio of completed projects and publications showcasing real-world problem-solving. You are proficient in python programming for data science (pandas, numpy, scipy, scikit-learn, statsmodels). You are an expert in statistical analysis and machine learning with deep understanding of algorithms, methods, and their practical applications. You are proficient in SQL and database operations for data manipulation and analysis.You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases).You have good understanding of MLOps practices and model deployment workflows.You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain).Your level of English is advanced (C1) or above.You are ready to learn new methods, able to switch between tasks and topics quickly and sometimes work with challenging, complex guidelines.Our freelance role is fully remote so, you just need a laptop, internet connection, time available and enthusiasm to take on a challenge.BenefitsWhy this freelance opportunity might be a great fit for you? Take part in a part-time, remote, freelance project that fits around your primary professional or academic commitments.Work on advanced AI projects and gain valuable experience that enhances your portfolio.Influence how future AI models understand and communicate in your field of expertise.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level mechanical engineering problems grounded in real practice.Evaluate AI-generated solutions for correctness, assumptions, and engineering logic.Validate analytical or numerical results using Python (NumPy, SciPy, Pandas).Improve AI reasoning to align with first principles and accepted engineering standards.Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for mechanical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Mechanical Engineering or related fields, e.g. Thermodynamics, Fluid Mechanics, Mechanical Design, Computational Mechanics, etc. 3+ years of professional mechanical engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $20/hour*  Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.

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Please submit your CV in English and indicate your level of English proficiency. Mindrift connects specialists with project-based AI opportunities for leading tech companies, focused on testing, evaluating, and improving AI systems. Participation isproject-based, not permanent employment.What this opportunity involves While each project involves unique tasks, contributors may: Design graduate- and industry-level mechanical engineering problems grounded in real practice.Evaluate AI-generated solutions for correctness, assumptions, and engineering logic.Validate analytical or numerical results using Python (NumPy, SciPy, Pandas).Improve AI reasoning to align with first principles and accepted engineering standards.Apply structured scoring criteria to assess multi-step problem solving. What we look for This opportunity is a good fit for mechanical engineers with an experience in python open to part-time, non-permanent projects. Ideally, contributors will have:  Degree in Mechanical Engineering or related fields, e.g. Thermodynamics, Fluid Mechanics, Mechanical Design, Computational Mechanics, etc. 3+ years of professional mechanical engineering experience Strong written English (C1/C2) Strong Python proficiency for numerical validation Stable internet connection  Professional certifications (e.g., PE, CEng, PMP) and experience in international or applied projects are an advantage.How it works Apply → Pass qualification(s) → Join a project → Complete tasks → Get paidProject time expectations For this project, tasks are estimated to require around 10–20 hours per week during active phases, based on project requirements. This is an estimate, not a guaranteed workload, and applies only while the project is active. Payment Paid contributions, with rates up to $40/hour*  Fixed project rate or individual rates, depending on the project Some projects include incentive payments *Note: Rates vary based on expertise, skills assessment, location, project needs, and other factors. Higher rates may be offered to highly specialized experts. Lower rates may apply during onboarding or non-core project phases. Payment details are shared per project.