Senior/Lead Machine Learning Engineer

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

📋 Description

• Convert raw recorded data into clean, structured, and anonymized datasets for downstream teams.

• Take ownership of essential components of machine learning pipelines from start to finish.

• Enhance pipeline accuracy, cost-effectiveness, and reliability.

• Create evaluations and establish LLM judges.

• Conduct experiments and transform promising findings into validated enhancements for production.

• Assess and refine open-source models.

• Develop smaller, task-specific models.

• Manage, troubleshoot, and enhance production pipelines.

• Design and iterate on LLM evaluations and systems that utilize LLM as judges, including datasets, metrics, and benchmarks.

• Experiment with prompts, pipeline architecture, model selection, and inputs such as OCR text versus images combined with OCR.

• Propel LLM efficiency improvements by comparing models, restructuring processes, and substituting LLM calls with smaller, purpose-built models.

• Broaden the anonymization pipeline by assessing and modifying existing models.

• Collaborate with Python developers and quality engineers to implement experiments into production.

• Share accountability for the production code that is deployed.

• Document insights in experiment reports and design documentation.

⛳️ Requirements

• Strong foundation in machine learning and data science, including experimental design, data segmentation, metrics, bias, and statistical significance.

• Practical experience in applying LLMs in production or near-production environments, particularly in their evaluation.

• Proficiency in constructing evaluation sets, LLM judges, benchmarks, and iterating on prompts and pipelines.

• Comfort with exploring, troubleshooting, and transforming inconsistent data into measurable enhancements.

• Proficient in Python with solid engineering capabilities.

• Ability to produce clear, readable, and tested code suitable for production environments.

• Capacity to independently tackle ambiguous problems.

• Effective utilization of AI coding tools while taking responsibility for the delivered output.

• Proficient spoken and written English communication skills.

• Capability to articulate technical trade-offs to both technical and non-technical stakeholders.

• Experience in classical machine learning or deep learning model development (preferred).

• Familiarity with image/OCR pipelines or face-related anonymization (preferred).

• Background in deploying end-to-end ML features within a startup or scale-up setting (preferred).

🏝️ Benefits

• Competitive compensation package along with stock options.

• Flexible work arrangements: Work from anywhere—fully remote, at our hubs, or a combination of both.

• Company-provided laptop.

• Stipend for remote setup.

• Budget for co-working spaces.

• Flexible schedules and locations.

• Generous paid time off, in addition to local public holidays.

• Enhanced parental leave.

• Health and retirement benefits.

• Annual budget for learning and development.

• Annual workaway opportunities.

• Regular virtual and in-person social events.

• Chance to contribute to innovative projects that shape the future of work.