Drive the design, development, and deployment of advanced ML and AI solutions, with an emphasis on large language models (LLMs), deep learning architectures, and sophisticated statistical modeling.
Build scalable, robust data science systems—from data ingestion, data curation, data modeling to algorithm development, model deployment and monitoring—meeting enterprise-grade performance, reliability, and compliance standards.
Act as a subject matter expert, collaborating with data scientists, ML engineers, analysts, and business stakeholders to understand needs, define requirements, and deliver practical solutions with measurable business impact.
Effectively articulate complex technical concepts to non-technical partners, bridging gaps between technical teams and business operations for maximum results.
Drive adoption of best practices in MLOps, including CI/CD pipelines, containerization, orchestration, observability, and reproducibility.
Oversee and enhance the integrity, security, and compliance of all data science workflows and contracts.
Stay abreast of the latest industry advancements in ML, LLMs, deep learning, cloud data engineering, and MLOps solutions (AWS, Kubernetes, Snowflake, etc.).

3+ years’ experience in Data Science, Machine Learning, or a related field
BA/BS in Computer Science, Data Science, or related discipline (advanced degree is highly preferred)
Deep expertise in statistical modeling, machine learning, and deep learning (including practical experience with LLMs and transformers)
Strong programming skills (Python preferred; Java, Scala, or similar also valued)
Proven ability to build and optimize scalable data science solutions—end-to-end—from data pipelines (dbt, Astronomer, Snowflake, AWS) to deployment and monitoring (Docker, Kubernetes, CI/CD, MLOps best practices)
Experience handling and analyzing large datasets, with a preference for experience in cloud data warehouses (Snowflake)
Demonstrated success in translating business needs into analytical solutions, driving quantifiable impact
Strong stakeholder engagement skills, with a track record of building trusted business partnerships and driving adoption of data science initiatives
Exceptional ability to simplify and communicate complex data science concepts to technical and non-technical audiences alike
Experience working cross-functionally with engineers, analysts, and product leaders
Steadfast commitment to continuous learning, collaboration, and fostering an inclusive, innovative team environment.

Opportunity to develop and scale of LLM and deep learning solutions with real-world business impact
An environment that values innovation, ownership, and professional growth
The chance to work on high-visibility, high-impact projects at scale alongside a passionate multidisciplinary team

Senior Machine Learning Engineer

Key skills