Role overview
Our client is seeking a
Lead ML Engineer
to join our ML team within the Data Science group. As a Lead ML Engineer, you will contribute to the deployment, monitoring, and management of machine learning models and data pipelines. You will work with a peer group of ML engineers to develop ML modules and end-to-end engineering solutions. Candidates must be able to work on a hybrid basis in NYC or NJ and live locally in the tristate area.
What you'll work on
- Architect, develop and manage machine learning model development and deployment lifecycle to launch GenAI and ML services end to end.
- Work on large-scale stateful and stateless distributed systems, including infrastructure, data ingestion platforms, SQL and no-SQL databases, microservices, orchestration services and more.
- Collaborate with cross-functional teams to integrate machine learning models into production systems.
- Create and manage Documentation and knowledge base, including development best practices, MLOps/LLMOps processes and procedures.
- Work closely with members of technology teams in the development and implementation of Enterprise AI platform.
- Fine Tune and Optimize Models: Adjust and refine generative AI models to enhance performance, adapt to new data, or meet specific use case requirements.
What we're looking for
- Bachelor’s degree in computer science, Engineering, or a related field.
- 8+ years of progressive experience as a data analytics, machine learning engineer or similar roles.
- A minimum of 5 years of experience in data science, data analytics, or related field.
- 5 years of relevant experience with
- Writing production level, scalable code with Python (or scala)
- MLOps/LLMOps, machine learning engineering, Big Data, or a related role.
- Elasticsearch, SQL, NoSQL, Apache Airflow, Apache Spark, Kafka, Databricks, MLflow.
- Containerization, Kubernetes, cloud platforms, CI/CD and workflow orchestration tools.
- Distributed systems programming, AI/ML solutions architecture, Microservices architecture experience.
- 2-3 years of experience with operationalizing data-driven pipelines for large scale batch and stream processing analytics solutions (Preferred).
- Experience with contributing to open-source initiatives or in research projects and/or participation in Kaggle competitions (Preferred).
- 6-12 months of experience working with RAG pipelines, prompt engineering and/or Generative AI use cases. (Preferred).
*After you've applied, connect directly to the recruiter at
https://www.linkedin.com/in/jpandya/
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning Data Science Data Engineer Generative Ai