Manager, Machine Learning Engineering

Summary

Join Fieldguide as a Machine Learning Engineering Manager and lead a team of approximately five machine learning engineers. You will leverage your expertise in ML and generative AI to drive critical AI initiatives, overseeing the delivery of ML-driven product features. Collaborate with product and design leaders to shape the AI roadmap and ensure alignment with business objectives. Guide the team on best practices for building generative AI systems, and establish frameworks for evaluating model performance. Participate in hiring and talent development, fostering an inclusive and high-performing team culture. This role offers the opportunity to build and scale a high-impact ML team at a rapidly growing Series B-stage startup.

Requirements

• Leadership and ML expertise: 8+ years of experience in applied machine learning (or related field), including at least 2+ years in a tech lead or people manager role . Proven ability to lead and develop engineering talent in a fast-paced environment
• Generative AI & NLP skills: Deep understanding of modern NLP, large language models (LLMs), and generative AI systems . Hands-on experience with prompt engineering for LLMs and developing evaluation frameworks to measure and improve model performance and quality
• Strong technical foundation: Proficiency in Python and ML libraries/frameworks, with a track record of building, deploying, and scaling ML solutions in production. Solid grasp of data engineering (ETL pipelines, data quality) and MLOps best practices for model deployment and monitoring
• People management excellence: Demonstrated ability to mentor, coach, and manage engineers effectively. Experience conducting performance reviews, providing constructive feedback, and guiding career growth for a technical team
• Exceptional communication: Excellent collaboration and communication skills. Comfortable working cross-functionally with product managers, designers, and other stakeholders to translate business needs into ML solutions and to clearly communicate complex concepts to non-engineers
• Strategic and analytical mindset: Adept at thinking big-picture about AI strategy while also able to dive into details. Strong problem-solving skills and decision-making judgment, especially in balancing quick wins vs. long-term research investments
• Culture and values alignment: Passion for building an inclusive, high-performing team culture. Embody Fieldguide’s values (Fearless, Fast, Lovable, Owners, Win-Win, Inclusive) in your leadership style, and excited to help shape a remote-first, mission-driven team

Responsibilities

• Lead and mentor the ML team: Manage a team of ~5 Machine Learning Engineers, providing coaching, mentorship, and support. Foster an inclusive, psychologically safe team culture that enables growth and high performance
• Deliver AI-powered features: Oversee the end-to-end delivery of ML-driven product features (especially NLP and generative AI solutions) across multiple teams. Ensure projects are executed with high quality, reliability, and on schedule
• Strategic collaboration: Work closely with Product Managers, Designers, and the Head of Engineering to plan roadmaps, define our AI strategy, and integrate ML capabilities into the product. Align the team’s efforts with company goals and customer needs through cross-functional collaboration
• Technical guidance: Provide technical direction in ML architecture and design decisions. Guide the team on best practices for building generative AI systems, including effective prompt engineering techniques and robust solution design (while empowering individual engineers to own implementations)
• Quality and evaluation: Establish and champion frameworks for evaluating model performance and accuracy. Ensure our generative AI models and features are rigorously tested, monitored, and continually improved based on clear metrics and user feedback
• Hiring and team growth: Participate in hiring loops to attract and onboard top ML engineering talent. Set clear expectations for team members, and help scale the team by refining our hiring, interview, and onboarding processes
• Talent development: Own the career development and performance management process for your team. Conduct regular 1:1s and performance reviews, deliver actionable feedback, and create growth plans that advance each engineer’s skills and career path
• Continuous improvement: Refine team processes and workflows for efficiency and quality (e.g. code reviews, research spikes, deployment practices). Advocate for resources or process changes needed for the ML team to excel, and ensure the team’s work remains innovative, impactful, and aligned with Fieldguide’s high standards

Benefits

• Competitive compensation packages with meaningful ownership
• Flexible PTO
• 401k
• Wellness benefits, including a bundle of free therapy sessions
• Technology & Work from Home reimbursement
• Flexible work schedules