Machine Learning

Senior Product Manager (LLMs / AI Agents) $170,000 - $210,000+ (DOE) Boston, MA - Hybrid (2x days per week in-office) We’re partnered with a Series B AI company that’s reimagining how large enterprises deploy intelligent agents in regulated industries. Their platform enables Fortune 500 insurers and financial institutions to safely automate complex, multi-step workflows, from customer interactions to back-office processing, using powerful, enterprise-grade AI agents. As a Senior Product Manager, you’ll take ownership of critical parts of the roadmap shaping the next generation of AI agent technology. You’ll work at the intersection of product, engineering, and customer success, turning ideas into scalable tools that bring transparency, trust, and measurable ROI to enterprise automation. What You’ll DoDefine and deliver product features that help enterprises evaluate, supervise, and continuously improve their AI agents in production.Build intuitive AI-powered dashboards and reporting tools that offer deep visibility into performance, compliance, and customer outcomes.Partner with customers and internal teams to create agent-building experiences that feel seamless. Where configuration, testing, and deployment are guided by real-time AI assistance.Collaborate cross-functionally to launch and scale products that drive measurable value for Fortune 500 clients and high-growth startups alike.What We’re Looking For:4–7 years of relevant technical experience with at least 3 years in a PM role.Proven success shipping enterprise SaaS products, ideally in AI, data, or automation-heavy domains.Strong technical fluency, able to discuss APIs, data models, and system architecture confidently with engineering teams.Excellent communicator and collaborator, capable of influencing technical and executive stakeholders alike.Comfortable in fast-moving, high-growth environments where priorities shift and creativity thrives.Nice to Have:Experience with AI/ML platforms, contact center technology, or enterprise integrations.Previous startup or early-stage experience.Familiarity with regulated industries such as insurance, healthcare, or finance.Background in Computer Science, Engineering, or a related technical field.Apply now or reach out directly to benjamin@deeprec.ai for more details.

Machine Learning Engineer (LLM) $160,000 - $200,000+ (DOE) Boston, 2 days per week in-office We’re working a fast-growing AI company on a mission to automate complex workflows in the financial services sector, starting with insurance. Their technology leverages cutting-edge AI to simplify high-value processes, from multi-turn conversations to full workflow automation. As an ML Engineer within LLMs, you’ll be building and scaling advanced AI systems that power intelligent, multi-agent workflows. You’ll take ownership of designing, fine-tuning, and productionizing large language models, integrating them with backend systems, and optimizing their performance. You’ll collaborate closely with data science, DevOps, and leadership to shape the AI infrastructure that drives the company’s automation solutions. What You’ll Do:Build, fine-tune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows.Develop APIs, data pipelines, and orchestration systems for multi-agent, multi-turn AI conversations.Integrate models with backend services, including voice orchestration platforms and transcript generation.Optimize model usage and efficiency, transitioning from external APIs to in-house solutions.Collaborate cross-functionally with data scientists, DevOps, and leadership to deliver scalable machine learning solutions. What We’re Looking For:Essential Skills & Experience:Strong proficiency in Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).Hands-on experience fine-tuning LLMs (Hugging Face, PEFT).Familiarity with AWS (especially S3 for model management) and deploying ML models to production.Ability to reason deeply about ML principles, architectures, and design choices.Knowledge of multi-agent orchestration and conversational AI systems.Desirable Skills & Experience:Experience with RLHF or preference optimization.Background in voice AI, speech-to-text, or text-to-speech systems.Exposure to financial services or insurance applications.Familiarity with optimizing models for long-context scenarios. If you’d like to hear more, please apply or get in touch!

Machine Learning Engineer (LLM) Salary Competitive DOE Boston, 2 days per week in-office We’re working a fast-growing AI company on a mission to automate complex workflows in the financial services sector, starting with insurance. Their technology leverages cutting-edge AI to simplify high-value processes, from multi-turn conversations to full workflow automation. As an ML Engineer within LLMs, you’ll be building and scaling advanced AI systems that power intelligent, multi-agent workflows. You’ll take ownership of designing, fine-tuning, and productionizing large language models, integrating them with backend systems, and optimizing their performance. You’ll collaborate closely with data science, DevOps, and leadership to shape the AI infrastructure that drives the company’s automation solutions. What You’ll Do:Build, fine-tune, and productionize large language model (LLM) pipelines, including PEFT, RLHF, and DPO workflows.Develop APIs, data pipelines, and orchestration systems for multi-agent, multi-turn AI conversations.Integrate models with backend services, including voice orchestration platforms and transcript generation.Optimize model usage and efficiency, transitioning from external APIs to in-house solutions.Collaborate cross-functionally with data scientists, DevOps, and leadership to deliver scalable machine learning solutions. What We’re Looking For:Essential Skills & Experience:Strong proficiency in Python and ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch).Hands-on experience fine-tuning LLMs (Hugging Face, PEFT).Familiarity with AWS (especially S3 for model management) and deploying ML models to production.Ability to reason deeply about ML principles, architectures, and design choices.Knowledge of multi-agent orchestration and conversational AI systems.Desirable Skills & Experience:Experience with RLHF or preference optimization.Background in voice AI, speech-to-text, or text-to-speech systems.Exposure to financial services or insurance applications.Familiarity with optimizing models for long-context scenarios. If you’d like to hear more, please apply or get in touch!

Your Mission As a Senior ML/AI Engineer, you will lead the design, deployment, and scaling of ML/AI models in production. This is a high-ownership role where you will act as both a technical expert and a strategic thinker — ensuring delivery of robust, scalable models while aligning closely with stakeholder needs and business KPIs. You will work cross-functionally with both technical and business teams to craft tailored, high-impact AI solutions that drive real-world value. Responsibilities On the Business SidePartner with clients and internal stakeholders to understand strategic objectives and uncover ML/AI opportunities.Assess feasibility by analyzing available data sources and proposing realistic, impactful solutions.Define project goals, success criteria, and measurable KPIs in alignment with business needs.On the Technical SideLead the design and development of machine learning models using PyTorch, TensorFlow, or similar frameworks.Implement best-in-class MLOps practices to automate training, deployment, and monitoring of models (e.g., with Kubeflow).Build and optimize scalable pipelines for data ingestion, model training, evaluation, and inference.Ensure full automation from preprocessing to production, with robust testing and CI/CD integration.Collaborate closely with data engineers and platform teams to ensure model performance, reliability, and maintainability.Candidate Profile5+ years of hands-on experience in ML/AI engineering or data science roles.3+ years of experience with Google Cloud Platform (GCP), including hands-on use of Vertex AI and BigQuery.Proven experience delivering production-grade models and scalable ML systems.Strong knowledge of ML algorithms, model development, deployment, and lifecycle management.Proficiency in Python and ML frameworks such as TensorFlow or PyTorch.Expertise in MLOps tooling and automation (e.g., Kubeflow, MLflow, Vertex AI Pipelines).Experience applying LLMs, especially in Retrieval Augmented Generation (RAG) workflows.Familiarity with data preprocessing, model tuning, and performance optimization.Clear communicator with the ability to translate complex ideas to technical and non-technical audiences.Fluent in English (French or Spanish is a plus).Eligible to work in Europe.Bonus SkillsExperience with LangChain, LangGraph, or dbt.Prior involvement in consulting or client-facing AI/ML projects.Contribution to open-source or published work in AI/ML communities.Why Join The company values:Generosity – giving back through open-source and community initiatives.Transparency – every voice matters; decisions are shared and aligned.Growth – continuous learning and experimentation encouraged.Ownership – responsibility and impact are celebrated.Trust – people are valued as individuals, not just colleagues.Ever-learning – time is dedicated to innovation, training, and knowledge-sharing.This is an opportunity to grow, contribute, and make a meaningful impact — both inside the company and in the wider AI/ML community.

We are looking for an experienced Engineer/Scientist to join a cutting-edge robotics team in Zurich, focused on humanoid manipulation through state-of-the-art AI. You will contribute to developing and deploying learning-based controllers to enable robots to interact intelligently, reliably, and flexibly with complex environments. This role is deeply hands-on with real robot hardware, leveraging your expertise across vision-language-action (VLA) models, diffusion models, reinforcement learning, and dexterous manipulation. What we’re looking for:PhD or Master's in Robotics, AI, or related fieldsStrong expertise in learning-based dexterous manipulation (multi-fingered grasping, task-oriented manipulation)Practical experience with running real-time controllers on robotic hardwareDeep knowledge of diffusion models, transformers, CVAEs, normalizing flowsExperience working with ROS, PyTorch, and PythonFamiliarity with vision-language models (VLA/VLMs/LLMs) for robotic planning or failure detectionBonus: experience with synthetic data generation, simulation environments, teleoperation systemsWhy this role?Join a high-calibre team (ex-ETH / ex-NVIDIA founders) backed by significant investment (Seed + Series A secured)Work at the intersection of simulation, reinforcement learning, and robotics hardwareContribute to next-generation humanoid robots without reliance on traditional imitation learning paradigmsSignificant stock offering.If you’re passionate about building more intelligent robots through cutting-edge AI and want to work in a fast-moving, well-resourced environment, we’d love to hear from you.