Manager of Machine Learning Engineering
Confirmed on the employer's own hiring board on Oct 13, 2026. First seen by Alion on Sep 24, 2026.
Join Tala as the Manager of Machine Learning Engineering, where you will lead the ML Platform team and manage a group of Machine Learning Engineers. This player-coach role involves developing and growing the team while providing technical leadership in architecture, engineering practices, reliability, and production systems. You will focus on real-time machine learning inference, streaming data systems, and the platforms that support batch model development and deployment.
Missions
- Manage and develop a team of Machine Learning Engineers, providing technical leadership and guidance in architecture and engineering practices.
- Drive the development of platforms and frameworks that enable Data Scientists to train, deploy, monitor, and operate machine learning models at scale.
- Collaborate with cross-functional teams to translate business and technical needs into scalable ML platform solutions, coordinating dependencies and delivery.
Profil recherché
- Experience owning team goals, prioritization, estimation, and delivery- 2+ years of directly managing engineers, including hiring, performance management, coaching, and career development
- Experience managing a team through at least one full performance cycle
- Demonstrated ability to coach engineers toward promotion and address underperformance effectively
- Willingness to be actively involved in sourcing, interviewing, and closing engineering talent
- Experience with production on-call, incident response, and capacity planning
- Strong understanding of software quality, security, reliability, testing, and production operations
- Experience building and operating machine learning or causal inference systems in production
- Earlier-career experience personally building and deploying ML models or ML infrastructure
- At least 3 years of hands-on Python experience
- Ability to participate in technical architecture and system-design discussions and provide technical direction without needing to be the primary coder
- 6+ years of backend software engineering experience in consumer-scale applications
- Cloud & Infrastructure: AWS, GCP, Azure, Kubernetes, Docker
- Streaming: Kafka, Kinesis, Beam, Flink, Spark Streaming
- Languages: Python, SQL
- ML/Analytics: Machine learning, causal inference, scalable algorithms
- APIs: REST, GraphQL, gRPC, Protocol Buffers
- Production Engineering: DevOps, SLOs, monitoring/observability, on-call, capacity planning, root-cause analysis
- Batch Processing: Airflow, Metaflow
- Machine Learning: Jupyter, Pandas, Scikit-Learn, XGBoost, TensorFlow, PyTorch, Hugging Face
- Databases: MySQL, PostgreSQL, Cassandra, Snowflake, Druid, and/or similar technologies
- We’re particularly interested in candidates with experience across: