Senior Software Engineer, AI Voice Agent
As a Senior Software Engineer on the AI Voice Agent team, you will work on real-time systems involving live audio streaming and latency optimization integrated with speech providers. You will build and improve conversation intelligence systems that manage LLM layers, including prompt construction, context management, function calling, and dialogue management to create natural, actionable phone conversations. You will develop the action framework allowing configurable API calls with branching logic and runtime execution, supporting tasks like data lookup and ticket creation during calls. You'll manage knowledge ingestion, storage, and retrieval to enhance agent memory and learning over time. You will collaborate with designers to enable customers to create, configure, test, and deploy voice agents through intuitive product experiences. Additionally, you will help develop evaluation frameworks, analytics, call quality metrics, and monitoring instrumentation, and participate in on-call rotation duties.
Member of Technical Staff (Data): World Models
Design, automate, maintain, and optimize Python ETL pipelines (Spark/Ray) for large-scale multimodal data. Build and maintain data cataloging, lineage, quality tooling, integrity verification, access controls, and lifecycle management systems. Provide guidance, internal tools, and documentation to colleagues on data best practices. Serve as a custodian of the company’s datasets, ensuring overall data health, quality, and discoverability.
Product Manager (Agents)
Lead the Lovable agent end-to-end by owning quality, roadmap, and feedback loops to improve it. Represent the user by synthesizing findings on agent performance and behavior and communicating these to the team clearly. Run discovery processes including user interviews, competitive research, evaluation analysis, prompt experimentation, and messaging for new agent capabilities. Own the quality bar for agent outputs by driving evaluation infrastructure, monitoring regressions, and ensuring continuous improvement with every release. Scope features carefully to deliver the right functionality, validate through user feedback and metrics, and eliminate non-effective parts. Enable sales, support, and marketing teams with the necessary context to communicate new agent capabilities effectively. Initial projects include rebuilding the agent evaluation framework to catch regressions before release, discovering gaps in agent reliability and trust, and defining and shipping the first iteration of improved agent error recovery and communication.
Electrical Engineer & Python Expert - Freelance AI Trainer
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; and apply structured scoring criteria to multi-step problems.
Statistics Expert (Python) - Freelance AI Trainer
Contributors design rigorous statistics problems reflecting professional practice; evaluate AI solutions for correctness, assumptions, and constraints; validate calculations or simulations using Python libraries such as NumPy, Pandas, SciPy, Statsmodels, and Scikit-learn; improve AI reasoning to align with industry-standard logic; and apply structured scoring criteria to multi-step problems.
Penetration Tester
Plan and execute penetration tests across Lovable's web platform, mobile surface, APIs, cloud infrastructure, and AI pipelines. Probe LLM integrations for prompt injection, jailbreaks, data leakage, and novel attack vectors unique to AI-generated code running in live products. Identify systemic vulnerabilities introduced when millions of users create and deploy real applications on Lovable. Work directly with engineering to prioritise, remediate, and verify fixes, closing the loop between discovery and resolution. Run internal red team exercises, contribute to threat modelling, and embed an attacker's mindset across the engineering culture to raise the security bar organization-wide. Help make Lovable the most secure AI product in the market.
Forward Deployed Engineer - ML
As a Forward Deployed ML Engineer, you will work hands-on with companies such as Suno, Lovable, Cognition, and Meta to architect and optimize production AI workloads on Modal's platform. You will contribute to open-source projects like SGLang and publish technical content showcasing Modal's capabilities across the AI stack. Collaboration with Modal's product and sales teams is expected, serving both as an engineer and a product stakeholder. You will build trusted relationships with technical leaders including CTOs, VPs of Engineering, and ML leads at frontier AI companies. Additionally, you will conduct technical demos, experiments, and proof-of-concepts to demonstrate Modal's performance advantages.
Senior ML Operations (MLOps) Engineer
The Senior ML Operations (MLOps) Engineer at Eight Sleep is responsible for introducing and implementing cutting-edge ML technologies, owning the design and operation of robust ML infrastructure including scalable data, model, and deployment pipelines to ensure reliable model delivery to production. They collaborate cross-functionally with R&D, firmware, data, and backend teams to ensure reliable and scalable ML inference on Pods. They optimize ML systems for cost, scalability, and performance across training and inference, and develop tooling, microservices, and frameworks to streamline data processing, experimentation, and deployment. The role requires effective communication in a remote work environment.
Manual Quality Assurance Engineer, Web Core Product
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture that improve performance, latency, throughput, and efficiency of deployed models. Build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Safety Engineer
The AI Safety Engineer is responsible for designing and building scalable backend infrastructure for content moderation, abuse detection, and agents guardrails by deploying AI/ML models into production systems. They will architect robust APIs, data pipelines, and service architectures to support real-time and batch moderation workflows. The role includes implementing comprehensive monitoring, alerting, and observability systems, establishing SLIs, SLOs, and performance benchmarks. The engineer will collaborate with ML engineers to translate research models into production-ready systems and integrate them across the product suite. Additionally, they will drive technical decisions and contribute to the vision for the safety roadmap to build next-generation platform guardrails for scale and precision.
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