Responsibilities
- Collaborate with Product and Engineering teams to pinpoint high-value initiatives, clarify open-ended challenges, set performance benchmarks, and select practical methods including heuristics, statistical models, machine learning, or generative AI.
- Lead structured experimentation across teams by designing hypotheses, defining key metrics and safeguards, conducting power analyses, executing A/B or quasi-experimental tests, and delivering actionable results.
- Develop and refine machine learning and AI features for production use, such as classification, information extraction, ranking, recommendations, and generative components like retrieval-augmented generation or agent frameworks, balancing performance, speed, and cost.
- Implement rigorous evaluation standards for ML and large language models, including curated datasets, offline and online testing strategies, regression testing, and proactive monitoring for performance degradation.
- Guide engineering teams in the safe and effective use of AI by advising on prompt engineering, function calling, structured outputs, safety controls, and evaluation techniques.
- Design and implement agentic workflows where they provide tangible product benefits, ensuring defined boundaries, monitoring capabilities, and fallback mechanisms.
- Oversee the full lifecycle of deployed models and AI systems, from data needs and training or fine-tuning to validation, deployment, monitoring, incident response, and iterative enhancements.
- Amplify organizational impact by building reusable tools such as evaluation frameworks, shared datasets, templates, and documentation, and by leading training sessions.
- Convey analytical findings and strategic trade-offs clearly to both technical and non-technical audiences, enabling data-driven decisions and measurable outcomes.
- Advocate for ethical and privacy-conscious AI practices, including proper data handling, bias and fairness assessments, and human oversight when appropriate.
Benefits
- Competitive compensation package
- Fully remote work with hybrid flexibility and financial support for home office setup
- Access to coworking spaces via subscription for team collaboration
- Comprehensive health, dental, and life insurance coverage
- Unlimited vacation policy with adaptable holiday scheduling
- Paid leave for new parents to spend time with family
- Opportunities for career growth through internal and external training
Compensation
Salary determined by geographic zone and market benchmarks; varies by location
Work Arrangement
Remote (Worldwide) — with team hubs in San Francisco, New York, Boston, Paris, and London
Work Arrangement
This role is fully remote, with occasional in-person requirements for trainings, meetings, or team events as directed by management.
Other
- Benefit offerings vary by country or state of residence, are subject to eligibility, and may change over time.
- The company hires across multiple U.S. states and countries, using geographic zones and market data to set salary ranges based on the candidate’s home location.
- All inquiries about data processing at the company should be sent to HR@traackr.com.
Not specified
