Engineering Manager, Machine Learning
New
United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 8+ years of experience building machine learning or data-driven systems; 3+ years of experience managing ML engineers or data science teams
- Required Skills
- PythonArtificial IntelligenceMachine LearningPeople ManagementData scienceSoftware Engineering
Requirements
- 8+ years of experience building machine learning or data-driven systems.
- At least 3+ years of experience managing ML engineers or data science teams.
- Strong technical background in machine learning, data systems, or applied AI, with ability to guide technical decisions.
- Experience working with Python-based ML workflows and collaborating closely with data scientists and engineers.
- Proven leadership experience in high-growth startup or scale-up environments.
- Strong coaching and people management skills with experience developing engineering talent.
- Ability to operate in cross-functional environments with Product, Design, and Engineering stakeholders.
- Strong communication skills with the ability to align teams and influence technical direction.
- Product mindset with ability to connect technical work to measurable business and product impact.
- Passion for learning and staying current with advancements in ML and AI technologies.
Responsibilities
- Lead and scale multiple machine learning and data science teams delivering AI-driven and geospatial products.
- Define and drive technical direction while ensuring alignment with product strategy and long-term modeling needs.
- Oversee delivery of ML systems built on satellite imagery and large-scale geospatial datasets, balancing experimentation and production readiness.
- Build, coach, and develop high-performing teams through regular feedback, mentoring, and career development support.
- Partner closely with Product Managers to ensure technical decisions support both immediate delivery and future scalability.
- Collaborate with engineering, design, and leadership teams to evolve ML practices, workflows, and delivery standards.
- Drive hiring and talent strategy to attract and retain top machine learning and data engineering talent.
- Ensure teams operate efficiently, collaboratively, and with strong ownership of outcomes and execution quality.
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