Director of MLOPs Engineering

New York

  Machine Learning



Our client are a leader in the Financial Services industry delivers essential insights and solutions, fostering confident decision-making for governments, businesses and individuals. Their mission is to empower global customers in planning for the future by uncovering opportunities, overcoming challenges and providing clarity in intricate landscapes.

They are hiring a Director of MLOps Engineering to lead the Data Science team, driving the integration of advanced AI capabilities to elevate their products and services. The successful candidate will be pivotal in crafting and executing MLOps strategies, overseeing ML architecture design and leading the deployment of machine learning models into production environments.


  • As Director of MLOps Engineering, you will develop and implement MLOps strategies, best practices and standards to optimize AI ML model deployment and monitoring efficiency.

  • You will create roadmaps and strategies for MLOps and LLMOps Platforms, ensuring a seamless implementation throughout the model lifecycle.

  • Oversee the design, deployment and management of scalable and reliable infrastructure dedicated to model training and deployment.

  • Lead the deployment of machine learning models into production environments, prioritizing reliability and scalability.

  • Establish and sustain robust monitoring systems to track model performance, data quality and infrastructure health.

  • Collaborate closely with data scientists, machine learning engineers and software engineers to seamlessly integrate machine learning models into production systems.

  • Collaborate with business and PM stakeholders in roadmap planning and implementation efforts.

  • Recruit, develop and mentor technical AI/ML engineering talent to foster their professional growth within the team.


  • Bachelor’s or Master’s degree in Computer Science, Engineering or similar.

  • At least seven years of experience in roles such as ML engineer, architect, lead data scientist or similar positions within Big Data or public cloud platforms.

  • Minium of four years of hands-on experience in integrating, evaluating, deploying and operationalizing ML and LLM models at a scalable level.

  • Expertise in distributed computing, orchestration technology (Kubernetes, Ray, Airflow), and proficiency in public cloud platforms (AWS, GCP, Azure).

  • Proficiency in working with technologies such as Databricks, MLflow, Flink, or similar AI/ML/ML Ops tools.

  • Experience with SQL, NoSQL, ElasticSearch, MongoDB, Spark, Python, and PySpark for model development and ML Ops.

  • Excellent written and verbal communication skills, along with proficiency in stakeholder management and leadership abilities.

Salary: $150,000 – $230,000 DOE

If this sounds like the role for you, apply now in the link below or email your resume directly to