Responsibilities
- Define and drive the technical roadmap and long-term strategy for the ML Data Service platform, ensuring it meets the evolving needs of ML engineers across the company.
- Serve as the top technical expert for the team, architecting complex, highly scalable, and fault-tolerant systems for data ingestion, transformation, and serving.
- Lead the technical vision for the provision of diverse training data sources, including ingestion from real-world drive logs, resimulation outputs, autolabelling pipelines, and human labelling efforts.
- Drive the implementation of robust mechanisms for monitoring data quality, tracking data lineage, and ensuring overall data governance and compliance.
- Provide hands-on technical guidance, design reviews, and mentorship to engineers, ensuring the adoption of best practices, high code quality, and operational excellence.
- Manage a team of software engineers, including performance reviews, career development, coaching, and mentoring.
- Act as a technical leader-manager hybrid, balancing 50% management duties with 50% technical leadership, architecture, and hands-on coding/design.
- Drive hiring and recruitment efforts to attract, onboard, and retain top engineering talent, fostering a diverse and inclusive team culture.
- Champion engineering excellence, operational rigor, and a strong sense of ownership within the team.
- Collaborate closely with ML model teams and Infrastructure teams to understand data needs and deliver solutions that accelerate ML development cycles.
- Lead the execution of major projects, ensuring on-time delivery and alignment with business objectives.
- Communicate complex technical concepts and strategic direction effectively to both technical and non-technical stakeholders, including executive leadership.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
- 8+ years of experience in software engineering, with a strong focus on large-scale data systems, distributed systems, or ML infrastructure.
- 3+ years of experience managing engineering projects with a track record of delivering efficient tools and infra. Manager experience of building and scaling high-performing teams is a strong plus (including mentoring, performance management, and career development).
- Deep expertise in data processing technologies (e.g., Spark, Flink, Beam, distributed databases) and experience with cloud platforms (e.g., AWS, GCP, Azure).
- Demonstrated experience designing, implementing, and operating production-grade ML data pipelines or feature stores.
Benefits
- medical
- dental
- vision
- 401k with a company match
- health saving accounts
- life insurance
- pet insurance
Additional Information
- The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
