Engineering Manager, Active Learning
The Engineering Manager role at Deepgram involves leading the design and implementation of internal data and ML training systems. Responsibilities include recruiting, hiring, training, and supporting top engineering talent to build a world-class team; transforming cross-functional visions into detailed project plans with clarity on commitments, risks, and timelines; defining and owning technical strategy to accelerate ML training pipelines; promoting a strong team engineering culture focused on rigorous engineering standards and continuous improvement; partnering with DataOps and Research teams to design and implement new services, features, or products end to end; and coaching and mentoring engineers to support personal growth while achieving ambitious team goals.
Backend Engineer- Inference Services
The Backend Engineer is responsible for leading the design and implementation of Deepgram's products, specifically developing secure, robust, and scalable services for speech processing, distributed compute orchestration, and optimized scheduling. Responsibilities include improving Deepgram's core inference services in networking, speech processing, audio transcoding, and latency and memory optimization, developing processes for measuring, building, and optimizing services to maximize system performance, debugging complex system issues involving networking, scheduling, and high performance computing, rapidly customizing backend services to support customer needs, and partnering with Product to design and implement new services, features, and products end to end.
Research Engineer, Machine Learning Systems
The responsibilities include architecting and managing horizontally scalable systems to accelerate the end-to-end training lifecycle for Speech-to-Text (STT) and Text-to-Speech (TTS) models, focusing on optimized data preparation, high-throughput training pipelines, distributed infrastructure, and automated evaluation tooling. The role also involves designing and implementing internal UIs and tools to make ML systems and workflows accessible and transparent to non-technical stakeholders. Additionally, the position requires overseeing and managing training tooling, job orchestration, experiment tracking, and data storage.
Physics Researcher (Python) - Freelance AI Trainer
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.
Freelance AI Evaluation Engineer (Python/Full-Stack)
Create challenging coding test cases to push AI coding systems to their limits by reviewing and refining 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. Craft challenges that are fair but hard, where the AI has all the context it needs, requiring complex reasoning with information scattered across files and external sources. Analyze AI failures to understand the model's struggles and strengths. Iterate based on feedback from expert QA reviewers who score work on seven quality criteria.
Mathematics Researcher (Python) - Freelance AI Trainer
Contributors may design rigorous mathematics 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, and apply structured scoring criteria to multi-step problems.
AI & IT Systems Engineer
As Jasper undergoes an agentic AI shift, the AI & IT Systems Engineer role involves ensuring the IT infrastructure is robust, secure, and fine-tuned for advanced AI workflows, spending 70-80% of time on AI enablement deployments. Responsibilities include modernizing and improving IT systems to support autonomous AI workflows, building scalable automation infrastructure to enhance efficiency and reduce manual tasks, and operationalizing AI initiatives using tools like Claude, ChatGPT, and Zapier to create intelligent, cross-platform workflows involving platforms like Google Workspace and Slack. The role also requires managing core IT systems such as Identity Providers and Mobile Device Management, streamlining identity and access operations using features like Okta Workflows, and providing cross-functional technical support across departments to implement AI enablement projects. Additionally, the engineer manages a broad SaaS ecosystem, including Google Workspace and Linear, and assists in developing training resources and playbooks to facilitate team adoption of new AI tools.
Forward Deployed Engineer
The Forward Deployed Engineer is responsible for working closely with customers from onboarding through ongoing usage to help integrate and optimize AI solutions. They build new features, MVPs, and scalable solutions that impact customer outcomes, utilizing full-stack development skills in React, TypeScript, Node.js, and Python. They design, implement, and iterate on AI/ML applications including LLM prompting, tuning of voices, and transcribers. The role includes managing APIs and integrations with third-party systems to ensure seamless customer functionality. Collaboration with Product, Engineering, and Customer Success teams is essential to deliver tailored solutions. The engineer is expected to continuously iterate and improve AI solutions based on customer feedback and evolving requirements, while prioritizing and managing multiple projects under tight deadlines and maintaining high-quality results.
Senior Data Scientist
As a Senior Data Scientist, you will lead project teams delivering bespoke algorithms and high-stakes AI solutions to clients, conceive core data science approaches and design robust software architectures for new engagements, mentor a small number of data scientists and support their professional growth, partner with commercial teams to build client relationships and shape project scope for technical feasibility, contribute to Faculty’s thought leadership through courses, public speaking, or open-source projects, and ensure best practices are followed throughout project lifecycles to guarantee high-quality, impactful delivery.
Senior Machine Learning Engineer
Lead the exploration and application of Large Language Models and Generative AI, focusing on new areas within these fields. Translate the latest research into high-performing systems and models that can enhance user experiences. Help set the team's strategic direction, fostering an environment that encourages innovation and professional growth. Actively engage in all aspects of development including ideation, experimentation, implementation, and deployment. Collaborate with various teams and product managers to develop and implement ML-based solutions, ensuring performance optimization and alignment with broader business goals.
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