Senior Machine Learning Engineer - NYC

Senior Machine Learning Engineer - NYC

Base Salary: $220K base; $280–300K total comp 
Work Model: Hybrid, Midtown Manhattan (2–3 days on-site)

About the Role

We’re looking for an experienced Machine Learning Engineer to design, build, and scale intelligent data products that support real-world applications. This position bridges data engineering, model development, and productization — transforming large datasets and unstructured information into production-ready systems.

About the Client :

You’ll be joining a global organization that operates at the intersection of data, risk modeling, analytics, and financial advisory, supporting large enterprises in making high-impact strategic decisions. The team works with highly complex datasets and delivers advanced analytical and predictive solutions that directly influence business outcomes.

You’ll collaborate with engineering, product, and data teams to create end-to-end ML pipelines, optimize model performance, and drive experimentation with cutting-edge NLP and LLM techniques. This role is ideal for someone who thrives on building robust, scalable ML infrastructure from the ground up.

• Design and maintain scalable ETL/ELT pipelines to support analytical and ML systems.

• Build, train, validate, and deploy machine learning models with reproducible and automated workflows.

• Implement MLOps best practices, including packaging, orchestration, CI/CD, and production monitoring.

• Manage data structures, feature stores, and metadata to ensure high reliability and accessibility.

• Develop data products and APIs to expose ML insights to internal systems and stakeholders.

• Continuously optimize system performance, cost efficiency, and scalability across cloud environments.

• Establish standards for observability: logging, alerts, data lineage, documentation.

• Collaborate with product and business teams to define success metrics and measurable impact.

• Mentor engineers and data scientists in ML system design and operations.

• 7 years in machine learning engineering, data engineering, or applied data science.

• Degree in CS, Engineering, Math, Statistics, or equivalent experience.

• Advanced Python and SQL skills, with production-grade coding practices.

• Strong knowledge of testing, data validation, and ML quality assurance.

• Experience with cloud data platforms (Databricks, Snowflake, BigQuery).

• Familiarity with dbt or similar transformation frameworks.

• Expertise with scikit-learn, PyTorch, or Transformers for model development.

• Proven experience implementing MLOps workflows with CI/CD and containerization (K8s or serverless).

• Experience with NLP tools and techniques (spaCy, NLTK, prompt engineering).

• Proficiency integrating ML systems with REST APIs.

• Ability to design scalable and observable production ML systems.

• Experience mentoring or leading small technical teams.

• Experience deploying ML models at scale with latency/cost optimization.

• Background in consulting, tech, or fast-paced product environments.

• Familiarity with financial/risk modeling.

• Knowledge of BI tools (Looker, Tableau, Power BI).

• Experience with vector databases (e.g., LanceDB) and RAG pipelines.

• Experience using data labeling platforms like Label Studio.

You’ll help build the ML and data foundation of a global analytics-driven organization, influence architectural decisions, and work with cutting-edge NLP and generative AI technologies — all within a high-impact team focused on measurable business outcomes.