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Team Lead Machine Learning Jobs in New York (NOW HIRING)

J.P. Morgan

Lead Machine Learning Engineer-MLOps

New York, NY

$112K - $147K/yr

  • Medical

  • Retirement

As Lead Machine Learning Engineer on the Recommendation Engine team, you'll build and maintain pipelines for distributed model training on large compute clusters, batch/real-time model serving ...

PROPRIUS

Senior Machine Learning Engineer

New York, NY

$114K - $157K/yr

... now looking for a Lead Machine Learning Engineer to expand their capacity to next generation ... This is an opportunity to join a well-funded, highly regarded team who are partnered with and ...

Strivector Corp

Machine Learning

Manhattan, NY · On-site

They are seeking a Machine Learning professional capable of tackling research problems with ... Founded in 2011, the company is headquartered in Austin, USA, with a team of 51-200 employees. The ...

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Team Lead Machine Learning information

What is the difference between Team Lead Machine Learning vs Data Scientist?

AspectTeam Lead Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML, or related; experience in ML projectsBachelor's/Master's in CS, Statistics, or related; strong analytical skills
Work EnvironmentLeads ML teams, collaborates with engineers and product teamsAnalyzes data, builds models, reports insights
Employer & Industry UsageTech companies, AI startups, R&D divisionsFinance, healthcare, e-commerce, tech firms

While Data Scientists focus on analyzing data and building models, Team Lead Machine Learning oversees ML projects and manages teams. The roles often overlap, but the lead position emphasizes leadership and project management in ML initiatives.

Infographic showing various Team Lead Machine Learning job openings in New York as of August 2026, with employment types broken down into 100% Full Time. Highlights an 75% In-person, and 25% Hybrid job distribution.

Lead Machine Learning Engineer-MLOps

JPMorgan Chase & Co.

Manhattan, NY • On-site

$113K - $148K/yr

Other

Medical, Retirement

Re-posted 9 days ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 495 frontline employees who took The Breakroom Quiz

72nd of 171 rated banks

Job description


We are looking for a Senior MLOps engineer to work closely with Data Scientists to build and deploy ML models on a modern MLOps stack.
As Lead Machine Learning Engineer on the Recommendation Engine team, you'll build and maintain pipelines for distributed model training on large compute clusters, batch/real-time model serving, hyperparameter tuning at scale, model monitoring, production validation and other activities vital for model development, testing and deployment in a well-managed, controlled environment.
Our product, Personalization and Insights, builds and supports high throughput, low latency applications which leverage state of the art machine learning architectures, and which are deployed in AWS. These applications power personalized experiences across Chase Consumer & Community Banking channels, to help weave a user experience that includes traditional banking services with other services in the Travel, Merchant Offer Shopping, and Dining spaces.
Job responsibilities
  • Build, deploy, and maintain robust pipelines for distributed training on GPU-enabled clusters to support scalable machine learning workflows.

  • Develop and manage pipelines for high-throughput, real-time inference as well as batch inference, ensuring optimal performance and reliability.

  • Implement quantization techniques and deploy large language models (LLMs) to maximize efficiency and resource utilization.

  • Oversee the management and optimization of vector databases to support advanced AI and machine learning applications.

  • Establish and maintain comprehensive monitoring and observability pipelines to ensure system health, performance, and rapid issue resolution.

  • Collaborate with cross-functional teams to integrate new technologies and continuously improve existing infrastructure.

  • Partner with product, architecture, and other engineering teams to define scalable and performant technical solutions.

Required qualifications, capabilities, and skills
  • BS in Computer Science or related Engineering field with 6+ years of experience Or MS degree in Computer Science or related Engineering field with 4+ years experience.

  • Solid knowledge and extensive experience in Python and in cloud computing, preferably AWS
  • Understanding of quantization techniques such as PTQ, AWQ etc. used to quantize LLMs for accelerating inference on specific GPU architectures
  • Experience in systems engineering fundamentals: caching, CUDA, autoscaling, high throughput, low latency, x-region resilient applications
  • Deep knowledge and passion for data science fundamentals, training and deploying models

  • Experience in monitoring and observability tools to monitor model input/output and features stats

  • Operational experience in big data/ML tools such as Ray, DuckDB, Spark and in training/inference systems such as Ray, vllm/SGLang

  • Solid grounding in engineering fundamentals and analytical mindset

Preferred qualifications, capabilities, and skills
  • Experience with recommendation and personalization systems is a plus.
  • CUDA experience is a big plus

  • Solid fundamentals and experience in containers (docker ecosystem), container orchestration systems [Kubernetes, ECS], DAG orchestration [Airflow, Kubeflow etc]

  • Good knowledge of Databases

About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world.

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