Senior ML Engineer

This is a fully remote position, open to applicants in Portugal.

📋 Description

• Lead machine learning projects from start to finish, encompassing exploration, production deployment, and ongoing refinements.

• Develop and construct agentic LLM systems that incorporate tool usage, retrieval, and orchestration tailored for clinical environments.

• Create evaluation datasets, both offline and online harnesses, LLM-as-judge pipelines incorporating human review, and regression testing protocols.

• Enhance model quality through methods such as prompting, retrieval, distillation, or fine-tuning based on empirical evidence.

• Operate across the entire AI stack, which includes data preparation, model adaptation, serving, monitoring, and feedback loops in production.

• Collaborate with Product, Clinical, and Engineering teams to convert clinical needs into technical solutions.

• Conduct code reviews, disseminate knowledge, and mentor junior engineers.

⛳️ Requirements

• Proven experience in deploying machine learning systems to production that are utilized by end-users.

• Practical experience with LLMs in production settings, including prompting, retrieval, tool invocation, and agent-like workflows.

• Experience in constructing evaluation datasets and frameworks.

• Strong foundational knowledge in machine learning and the capacity to assess technical trade-offs.

• Ability to transform ambiguous challenges into effective production systems.

• Proficient coding skills suitable for production environments.

• Understanding of distributed systems.

• Capability to troubleshoot complex machine learning pipelines.

• Effective communication skills with both technical and clinical stakeholders.

• AI proficiency at least at the Explorer level (Level 1), applying AI daily to enhance personal productivity.

• Experience in fine-tuning or preference optimization (such as RLHF, DPO, or similar) is advantageous.

• Background in healthcare AI or experience in high-stakes domains is a plus.

• Experience in developing agent frameworks or evaluation tools from the ground up is a plus.

• Contributions to open source projects, technical writing, or other forms of knowledge sharing are considered a bonus.

🏝️ Benefits

• Benefits and perks that align with the country of the candidate's location, adhering to local regulations and market standards.

• Compensation may include performance-related bonuses, variable pay, or sales incentives.

• Potential for private company stock options, if applicable.