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Director Machine Learning Jobs in New York (NOW HIRING)

exacare ai

Machine Learning Engineer

New York, NY · On-site

About the Role We are looking for a Machine Learning Engineer, MLOps to help operationalize and ... Radical candor, zero politics We say what's true, early, and we keep communication direct and clean ...

Associated Press

Machine Learning Engineer

Manhattan, NY · On-site

$145K - $180K/yr

... scale machine learning systems at AP, helping to lay the foundation for our machine learning ... This is an individual contributing role who will report directly to our Director of Development ...

Associated Press

Machine Learning Engineer

New York, NY · Hybrid

$145K - $180K/yr

... scale machine learning systems at AP, helping to lay the foundation for our machine learning ... This is an individual contributing role who will report directly to our Director of Development ...

Associated Press

Machine Learning Engineer

Manhattan, NY · Hybrid

$145K - $180K/yr

... scale machine learning systems at AP, helping to lay the foundation for our machine learning ... This is an individual contributing role who will report directly to our Director of Development ...

Extend

Machine Learning Researcher

New York, NY · On-site

$200K - $350K/yr

As a Machine Learning Engineer at Extend, you'll be responsible for building state-of-the-art ... have direct relationship with customers. * Work directly with the CEO, CTO, and other founding ...

Orita

Senior Machine Learning Engineer

New York, NY · On-site +1

$180K - $250K/yr

... direct mail today, more coming soon ...). By messaging prospects and customers when they're ... The Role As a Senior Machine Learning Engineer at Orita, you will: * Build and Productionize Models

Oxman

Machine Learning Research Engineer

New York, NY · On-site

$142K - $184K/yr

Develop machine learning models for geospatial inference of key ecosystem metrics, leveraging ... Self-directed with an aptitude for nurturing collaborative teamwork across disciplines Required ...

exacare ai

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

About the Role We are looking for a Senior Machine Learning Engineer, MLOps to help operationalize ... Radical candor, zero politics We say what's true, early, and we keep communication direct and clean ...

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Director Machine Learning information

See New York salary details

$39.4K

$100.6K

$154.3K

How much do director machine learning jobs pay per year?

As of Jul 19, 2026, the average yearly pay for director machine learning in New York is $100,577.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,200.00 and $116,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Director Machine Learning position, and why are they important?

To thrive as a Director Machine Learning, you need advanced expertise in machine learning, statistics, data science, and leadership, typically supported by a master's or Ph.D. in a related field and several years of relevant industry experience. Familiarity with tools such as Python, TensorFlow or PyTorch, cloud platforms, and data management systems, as well as certifications like AWS Certified Machine Learning or Google Professional Machine Learning Engineer, are commonly required. Exceptional communication, strategic thinking, and team management skills distinguish top candidates in this role. These capabilities are essential for driving organizational AI initiatives, fostering high-performing teams, and delivering impactful business solutions.

What is a Director Machine Learning job?

A Director of Machine Learning leads teams in developing and deploying machine learning models to solve business challenges. They define the AI strategy, oversee research, and ensure models are scalable and ethical. This role requires expertise in machine learning, data science, and leadership, as well as collaboration with cross-functional teams. Directors also stay updated on industry advancements and drive innovation within their organizations.

What are the primary responsibilities and challenges faced by a Director of Machine Learning on a daily basis?

A Director of Machine Learning is typically responsible for overseeing the development and deployment of machine learning solutions, mentoring technical teams, setting strategic direction for AI initiatives, and ensuring the alignment of projects with organizational goals. Challenges often include balancing innovative research with business priorities, navigating evolving technology landscapes, and coordinating efforts across data science, engineering, and stakeholder teams. This role requires regular collaboration with product managers, executives, and cross-functional departments to prioritize initiatives and communicate complex technical concepts. Successful directors excel at fostering a culture of continuous learning, optimizing team productivity, and staying ahead in a fast-paced, rapidly changing field.

What are the most commonly searched types of Machine Learning jobs in New York? The most popular types of Machine Learning jobs in New York are:
What are popular job titles related to Director Machine Learning jobs in New York? For Director Machine Learning jobs in New York, the most frequently searched job titles are:
What job categories do people searching Director Machine Learning jobs in New York look for? The top searched job categories for Director Machine Learning jobs in New York are:
What cities in New York are hiring for Director Machine Learning jobs? Cities in New York with the most Director Machine Learning job openings:
Director Machine Learning jobs near you
Infographic showing various Director Machine Learning job openings in New York as of July 2026, with employment types broken down into 1% As Needed, 82% Full Time, 15% Part Time, 1% Temporary, and 1% Contract. Highlights an 93% Physical, 2% Hybrid, and 5% Remote job distribution, with an average salary of $100,577 per year, or $48.4 per hour.

Machine Learning Engineer

exacare ai

New York, NY • On-site

Full-time

Medical, Dental, Vision, PTO

Re-posted 22 days ago

Job description

About the Role
We are looking for a Machine Learning Engineer, MLOps to help operationalize and scale our machine learning systems. This is an engineering-focused role centered on building the workflows, infrastructure, and processes that enable ML to move from research into reliable production systems.
You will partner closely with research-oriented ML teammates and help turn their work into scalable, maintainable, and cost-effective production systems. This includes building and improving data pipelines, training pipelines, deployment workflows, monitoring systems, and supporting infrastructure that allow the team to move faster and operate ML systems with confidence.
This is not a research-first role. It is best suited for someone who is excited by the systems, tooling, and operational side of machine learning.
What You'll Do
  • Build and maintain the workflows and infrastructure that support the end-to-end ML lifecycle
  • Partner with researchers and ML practitioners to productionize models and enable faster iteration
  • Design, build, and improve data pipelines and training pipelines
  • Improve data processing, annotation workflows, and ML system efficiency
  • Deploy and maintain the background systems that support model training and inference
  • Build tooling and processes for monitoring model performance, system reliability, and operational health
  • Improve the scalability, observability, and reproducibility of ML systems
  • Optimize ML infrastructure for speed, reliability, and cost-efficiency
  • Identify bottlenecks in the ML workflow and automate or streamline manual processes
  • Help establish best practices around ML operations, deployment, and system performance

What You'll Bring
  • Proven (3+ years) of experience in machine learning engineering, MLOps, ML infrastructure, data engineering, or backend/platform engineering in ML environments
  • Experience supporting ML systems end to end, from model handoff through deployment and monitoring
  • Strong experience building and owning data pipelines, training pipelines, or other production workflows that support ML
  • Experience working closely with researchers, data scientists, or ML practitioners to productionize models
  • Strong software engineering fundamentals and experience building production systems
  • Experience with monitoring, debugging, and improving production ML or data systems
  • A track record of improving reliability, scalability, speed, and/or cost efficiency in ML systems
  • Comfort operating in a fast-moving, startup-style environment with a high degree of ownership

Benefits + Perks
  • Competitive salary and equity in a high-growth startup
  • Flexible PTO, take what you need
  • Medical, dental, and vision coverage
  • Great startup culture, including company off-sites
  • High-achieving team, including ex-Amazon engineers and alumni of Bain, BCG, Goldman Sachs, and more

An insight into our Core Values
Only the best belong here
We are unapologetic about talent. This should be the best team you have ever been on. Protecting that standard is how we honor each other's time, ambition, and craft.
We work even harder to keep our partners than we did to earn them initially
The work does not stop when a customer first onboards to our platform. It deepens over time. We partner with operators, listening and learning about real problems, and translate that into solutions that help them succeed in practice. We earn trust through consistent delivery.
We keep the patient downstream of every decision
At the end of the day, this is about the patient. We get there by deeply respecting and reflecting on our purpose: to develop software that aids teams in delivering better care.
Raise the bar on ownership
We grow because people here go beyond the minimum. We invest extra effort, care, and ownership into what we build.
The world is moving fast. We move faster.
This is a race. We work hard, we move early, and we stay ahead of problems and competitors. If we slow down, someone else will pass us.
Radical candor, zero politics
We say what's true, early, and we keep communication direct and clean so the team can move.
Bring good vibes and win together
We win as a team. We bring energy, support each other, and make the workplace somewhere people are excited to show up.
If this sounds like you, we'd love to have a chat!
#LI-Hybrid
About ExaCare AI
ExaCare AI is a leading health tech company on a mission to build the AI operating system for post-acute care. Our platform turns messy, unstructured referral packets into clear clinical insights and next steps, so teams can make faster, safer placement decisions with less administrative burden. Today, ExaCare AI powers more than 2000 facilities, and is growing rapidly.
We recently raised a $30M Series A led by Insight Partners, and are bringing world-class talent together to transform healthcare. If you like building, learning, and want to make a real impact, come join us!

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