Senior Level ML Software Engineer Jobs
Senior level ml software engineer jobs place experienced engineers in ownership positions, setting technical direction, making architectural decisions, and leading the projects and teams that ship production ML systems. Roles are concentrated across Technology & Software, Electronics & Hardware, and Banking & Financial Services, with a mix of on-site, remote, and hybrid settings, and employers like Apple, Netflix, and Pinterest hiring at this level now.
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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
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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 ML Software Engineer Jobs: Frequently Asked Questions
How do I get a senior level ml software engineer job?
Employers at this level look for candidates who have owned ML systems end-to-end, from problem framing through deployment and monitoring, not just model development. A strong portfolio of production impact, experience mentoring engineers, and the ability to articulate tradeoffs in system design give candidates a clear edge. Leading a cross-functional project or contributing to open-source ML infrastructure also signals readiness for senior ownership.
Which companies hire senior level ml software engineers?
Companies hiring senior level ml software engineers right now include Apple, Netflix, and Pinterest, based on current listings on Migrate Mate as of July 2026. Hiring at this level covers large technology companies, AI-focused startups, and enterprises in finance, healthcare, and retail that are scaling production ML capabilities.
Are there remote senior level ml software engineer jobs?
Yes, remote and hybrid options are common at the senior level. About 45% of senior level ml software engineer openings are remote or hybrid as of July 2026, reflecting how many teams have restructured around distributed engineering. On-site roles do exist, particularly at companies with sensitive data environments or hardware-adjacent ML work.
What makes a ml software engineer role senior level?
Senior level ml software engineer roles are defined by scope, ownership, and influence rather than task execution. Engineers at this level design systems, set technical standards, and make decisions that affect multiple teams or products. They are expected to mentor junior and mid-level engineers, lead technical reviews, and drive ML strategy in collaboration with product and data leadership.
Which industries hire the most senior level ml software engineers?
Senior Level ml software engineer 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 demand because they are applying ML at scale, requiring engineers who can build reliable, maintainable systems and translate business problems into production-grade solutions.