Senior Level Machine Learning Manager Jobs
Senior level machine learning manager jobs place experienced practitioners in charge of model strategy, platform direction, and the engineering or research teams that deliver production systems. Openings concentrate in Technology & Software, Electronics & Hardware, and Banking & Financial Services, with a mix of on-site, remote, and hybrid roles across the country, and employers like Apple, Netflix, and Pinterest hiring at this level now.
Find JobsOverview
Open roles566+
Top stateCalifornia
Top employerApple
Top cityRemote
Work type55% On-site
Top industryTechnology
Showing 5 of 566+ Senior Level Machine Learning Manager jobs
Associate Director, Machine Learning (Core Algorithms)
We won't show you this job again
New 1m ago
Whoop
Associate Director, Machine Learning (Core Algorithms)
Boston, Massachusetts
New 1m ago
Machine Learning Engineer
We won't show you this job again
New 1m ago
Colgate-Palmolive
Machine Learning Engineer
New York, New York
New 1m ago
Tech Lead, ML Infrastructure
We won't show you this job again
New 1m ago
NBCUniversal
Tech Lead, ML Infrastructure
New York, New York
New 1m ago
Principal Machine Learning Engineer, Content ML, Level 7
We won't show you this job again
New 1m ago
Snap Inc.
Principal Machine Learning Engineer, Content ML, Level 7
Los Angeles, California
New 1m ago
Staff Machine Learning Engineer - Leasing
We won't show you this job again
New 1m ago
AppFolio
Staff Machine Learning Engineer - Leasing
Chicago, Illinois
New 1m ago
New 1m ago
Associate Director, Machine Learning (Core Algorithms)
Whoop·Boston, Massachusetts
Job functions:
$200k - $245k/yr
8+ yrs exp.
Full Time
Job Description
At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer through a deeper understanding of their bodies and daily lives.
We are seeking an Associate Director, Core Algorithms (Cloud) to lead the teams responsible for WHOOP's cloud-based algorithmic intelligence — the models and systems that transform physiological data into the sleep, recovery, and training insights our members rely on daily. This role is also responsible for ensuring our cloud algorithms evolve alongside WHOOP hardware, partnering with Sensor Intelligence and Hardware teams to translate new sensor capabilities into production-grade algorithmic experiences.
You will own the technical vision, execution, and organizational health of this team. You'll drive the evolution of our core production algorithms such as workout detection, strain, and sleep staging toward higher accuracy, better member experiences, and more mature development practices. You will partner closely with ML Platform, Sensor Intelligence, Research, Product, and Software Engineering to define what WHOOP algorithms can enable — not just how they perform technically, but how they show up for members.
This is a role for someone who has built and shipped physiological ML at scale in a consumer product, who has a deep product instinct for what algorithms mean to end users, and who knows how to elevate an ML organization's practices: raising the bar on tooling, processes, and standards to match the ambition of the work.
RESPONSIBILITIES
- Lead the cloud ML team responsible for the algorithms powering sleep, recovery, and training
- Directly manage applied ML scientists and ML engineers; provide coaching, career development, and performance feedback that grows individual contributors into strong technical leaders
- Ensure the technical quality bar for algorithm development is maintained by establishing the processes, reviews, and standards that guarantee rigor from research through deployment, and diving into designs and architectural decisions where necessary
- Help drive the vision for what WHOOP algorithms and next-generation sensors can enable; advocate for member experience and push the boundaries of what our data makes possible
- Ensure cloud algorithms remain compatible with future hardware generations; partner with Sensor Intelligence and Hardware to evolve proof-of-concept algorithms that leverage new sensor capabilities and bring them to production readiness
- Establish and improve development lifecycle practices: experiment management, model validation, deployment pipelines, and production monitoring
Partner with ML Platform / MLOps to define requirements and drive maturity improvements across experiment tracking, model monitoring, deployment automation, and observability
- Drive cross-functional alignment with Sensor Intelligence, Product, Software Engineering, and Research teams
QUALIFICATIONS
- 8+ years of experience in machine learning or applied data science, with hands-on experience developing and shipping ML models for a consumer product
- 4+ years of people leadership experience directly managing machine learning scientists/engineers, with demonstrated growth of team members and a track record of building high-performing teams
- Experience scaling a production ML organization: growing teams and leaders, identifying gaps in the development lifecycle, and driving improvements that increase velocity, reliability, and rigor
- Deep product sense: ability to think about algorithms from the member's perspective, drive the vision for what algorithms can enable, and ensure the team is building toward meaningful user outcomes
- Ability to evaluate technical designs, guide architectural decisions, and ensure quality at the system level, without needing to write code day-to-day
- Experience defining and driving cross-functional programs with engineering, product, and science partners
- Strong communication skills with the ability to translate complex ML concepts to diverse audiences including product, engineering, and executive stakeholders
PREFERRED
- Experience building algorithms using physiological or wearable sensor data (e.g., PPG, accelerometer, temperature, bioimpedance)
- Experience managing through hardware-coupled development timelines where sensor availability and device generations constrain algorithm roadmaps
- Familiarity with time-series modeling, sequential data, and the specific challenges of continuous physiological monitoring
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $200,000-$245,000 Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
Learn more about WHOOP.
Whoop
Associate Director, Machine Learning (Core Algorithms)
Boston, Massachusetts
New 1m ago
Job functions:
$200k - $245k/yr
8+ yrs exp.
Full Time
Job Description
At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP empowers members to perform at a higher level and live longer through a deeper understanding of their bodies and daily lives.
We are seeking an Associate Director, Core Algorithms (Cloud) to lead the teams responsible for WHOOP's cloud-based algorithmic intelligence — the models and systems that transform physiological data into the sleep, recovery, and training insights our members rely on daily. This role is also responsible for ensuring our cloud algorithms evolve alongside WHOOP hardware, partnering with Sensor Intelligence and Hardware teams to translate new sensor capabilities into production-grade algorithmic experiences.
You will own the technical vision, execution, and organizational health of this team. You'll drive the evolution of our core production algorithms such as workout detection, strain, and sleep staging toward higher accuracy, better member experiences, and more mature development practices. You will partner closely with ML Platform, Sensor Intelligence, Research, Product, and Software Engineering to define what WHOOP algorithms can enable — not just how they perform technically, but how they show up for members.
This is a role for someone who has built and shipped physiological ML at scale in a consumer product, who has a deep product instinct for what algorithms mean to end users, and who knows how to elevate an ML organization's practices: raising the bar on tooling, processes, and standards to match the ambition of the work.
RESPONSIBILITIES
- Lead the cloud ML team responsible for the algorithms powering sleep, recovery, and training
- Directly manage applied ML scientists and ML engineers; provide coaching, career development, and performance feedback that grows individual contributors into strong technical leaders
- Ensure the technical quality bar for algorithm development is maintained by establishing the processes, reviews, and standards that guarantee rigor from research through deployment, and diving into designs and architectural decisions where necessary
- Help drive the vision for what WHOOP algorithms and next-generation sensors can enable; advocate for member experience and push the boundaries of what our data makes possible
- Ensure cloud algorithms remain compatible with future hardware generations; partner with Sensor Intelligence and Hardware to evolve proof-of-concept algorithms that leverage new sensor capabilities and bring them to production readiness
- Establish and improve development lifecycle practices: experiment management, model validation, deployment pipelines, and production monitoring
Partner with ML Platform / MLOps to define requirements and drive maturity improvements across experiment tracking, model monitoring, deployment automation, and observability
- Drive cross-functional alignment with Sensor Intelligence, Product, Software Engineering, and Research teams
QUALIFICATIONS
- 8+ years of experience in machine learning or applied data science, with hands-on experience developing and shipping ML models for a consumer product
- 4+ years of people leadership experience directly managing machine learning scientists/engineers, with demonstrated growth of team members and a track record of building high-performing teams
- Experience scaling a production ML organization: growing teams and leaders, identifying gaps in the development lifecycle, and driving improvements that increase velocity, reliability, and rigor
- Deep product sense: ability to think about algorithms from the member's perspective, drive the vision for what algorithms can enable, and ensure the team is building toward meaningful user outcomes
- Ability to evaluate technical designs, guide architectural decisions, and ensure quality at the system level, without needing to write code day-to-day
- Experience defining and driving cross-functional programs with engineering, product, and science partners
- Strong communication skills with the ability to translate complex ML concepts to diverse audiences including product, engineering, and executive stakeholders
PREFERRED
- Experience building algorithms using physiological or wearable sensor data (e.g., PPG, accelerometer, temperature, bioimpedance)
- Experience managing through hardware-coupled development timelines where sensor availability and device generations constrain algorithm roadmaps
- Familiarity with time-series modeling, sequential data, and the specific challenges of continuous physiological monitoring
This role is based in the WHOOP office located in Boston, MA. The successful candidate must be prepared to relocate if necessary to work out of the Boston, MA office.
Interested in the role, but don’t meet every qualification? We encourage you to still apply! At WHOOP, we believe there is much more to a candidate than what is written on paper, and we value character as much as experience. As we continue to build a diverse and inclusive environment, we encourage anyone who is interested in this role to apply.
WHOOP is an Equal Opportunity Employer and participates in E-verify to determine employment eligibility. It is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.
At WHOOP, we view total compensation as the combination of base salary, equity, and benefits, with equity serving as a key differentiator that aligns our employees with the long-term success of the company and allows every member of our corporate team to own part of WHOOP and share in the company’s long-term growth and success.
The U.S. base salary range for this full-time position is $200,000-$245,000 Salary ranges are determined by role, level, and location. Within each range, individual pay is based on factors such as job-related skills, experience, performance, and relevant education or training.
In addition to the base salary, the successful candidate will also receive benefits and a generous equity package.
These ranges may be modified in the future to reflect evolving market conditions and organizational needs. While most offers will typically fall toward the starting point of the range, total compensation will depend on the candidate’s specific qualifications, expertise, and alignment with the role’s requirements.
Learn more about WHOOP.
See All 566+ Senior Level Machine Learning Manager Jobs
Find roles that match your experience and apply in just a few clicks.
Find JobsSenior Level Machine Learning Manager Job Market
Who's Hiring
- Apple63
- Netflix13
- Pinterest13
- Adobe12
- SentiLink12
Top Industries Hiring
- Technology & Software250
- Electronics & Hardware65
- Banking & Financial Services42
- Consulting & Professional Services28
- Media & Entertainment27
Senior Level Machine Learning Manager Jobs: Frequently Asked Questions
How do I get a senior level machine learning manager job?
Candidates who land these roles can point to a portfolio of shipped ML systems at scale, not just research or prototypes. Employers at this level want evidence of technical leadership: setting modeling strategy, resolving architectural trade-offs, and growing the engineers around you. A strong application connects your past ownership of outcomes directly to the team or platform scope in the job description.
Which companies hire senior level machine learning managers?
Companies hiring senior level machine learning managers right now include Apple, Netflix, and Pinterest, based on current listings on Migrate Mate as of July 2026. Hiring at this level comes from a wide range of employers, including large technology companies building internal AI platforms, financial institutions scaling predictive modeling, and growth-stage product companies maturing their ML infrastructure.
Are there remote senior level machine learning manager jobs?
Yes, though availability varies by employer and team structure. About 45% of senior level machine learning manager openings are remote or hybrid as of July 2026, reflecting how many organizations have built distributed ML teams. Fully remote roles at this level often come with expectations of occasional on-site presence for planning cycles or cross-functional alignment.
What makes a machine learning manager role senior level?
Senior level machine learning manager roles are defined by scope and ownership rather than task execution. You are expected to set the technical direction for a team or platform, make architectural decisions that affect multiple systems, and develop the people reporting to you. The distinction from a mid-level role is that you are accountable for outcomes across a function, not just your own deliverables.
Which industries hire the most senior level machine learning managers?
Senior Level machine learning manager roles concentrate in Technology & Software, Electronics & Hardware, and Banking & Financial Services, based on current listings on Migrate Mate as of July 2026. These sectors drive hiring at this level because they operate ML systems at a scale that requires dedicated technical leadership to maintain reliability, improve model performance, and align research priorities with business objectives.