Senior Platform Machine Learning Engineer Jobs

New

Senior ML Platform Engineer

At WHOOP, we're on a mission to unlock human performance and healthspan. WHOOP e...

Location

United States , Boston

Salary:

150000.00 - 210000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s Degree in Computer Science, Engineering, or a related field
or equivalent practical experience
5+ years of experience in software engineering with a focus on ML infrastructure, cloud platforms, or MLOps
Strong programming skills in Python, with experience in building distributed systems and REST/gRPC APIs
Deep knowledge of cloud-native services and infrastructure-as-code (e.g., AWS CDK, Terraform, CloudFormation)
Hands-on experience with model deployment platforms such as AWS SageMaker, Vertex AI, or Kubernetes-based serving stacks
Proficiency in ML lifecycle tools (MLflow, Weights & Biases, BentoML) and containerization strategies (Docker, Kubernetes)
Understanding of data engineering and ingestion pipelines, with ability to interface with data lakes, feature stores, and streaming systems
Proven ability to work cross-functionally with Data Science, Data Platform, and Software Engineering teams, influencing decisions and driving alignment
Passion for AI and automation to solve real-world problems and improve operational workflows

Job Responsibility

Architect, build, own, and operate scalable ML infrastructure in cloud environments (e.g., AWS), optimizing for speed, observability, cost, and reproducibility
Create, support, and maintain core MLOps infrastructure (e.g., MLflow, feature store, experiment tracking, model registry), ensuring reliability, scalability, and long-term sustainability
Develop, evolve, and operate MLOps platforms and frameworks that standardize model deployment, versioning, drift detection, and lifecycle management at scale
Implement and continuously maintain end-to-end CI/CD pipelines for ML models using orchestration tools (e.g., Prefect, Airflow, Argo Workflows), ensuring robust testing, reproducibility, and traceability
Partner closely with Data Science, Sensor Intelligence, and Data Platform teams to operationalize and support model development, deployment, and monitoring workflows
Build, manage, and maintain both real-time and batch inference infrastructure, supporting diverse use cases from physiological analytics to personalized feedback loops for WHOOP members
Design, implement, and own automated observability tooling (e.g., for model latency, data drift, accuracy degradation), integrating metrics, logging, and alerting with existing platforms
Leverage AI-powered tools and automation to reduce operational overhead, enhance developer productivity, and accelerate model release cycles
Contribute to and maintain internal platform documentation, SDKs, and training materials, enabling self-service capabilities for model deployment and experimentation
Continuously evaluate and integrate emerging technologies and deployment strategies, influencing WHOOP’s roadmap for AI-driven platform efficiency, reliability, and scale

What we offer

equity
benefits

Fulltime

New

Senior Machine Learning Engineer (Health)

WHOOP is an advanced health and fitness wearable, on a mission to unlock human p...

Location

United States , Boston

Salary:

150000.00 - 210000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor’s Degree in Computer Science, Data Science, Applied Mathematics, or a related field. Master’s preferred
5+ years of professional experience as a Machine Learning Engineer or Software Engineer with focus on ML systems
Proven expertise working with time series data (wearable, physiological, or high-frequency sensor data strongly preferred)
Experience designing and deploying ML inference systems at scale: both real-time streaming and large-scale batch pipelines
Strong coding skills in Python (scientific stack) and SQL, with a track record of writing clean, production-quality code
Strong communication skills to collaborate across engineering, research, and product teams
Proven experience deploying and maintaining ML systems on cloud platforms (AWS or GCP)
Working familiarity with MLOps best practices: model versioning, CI/CD for ML, observability, and monitoring for inference systems
Ability to reason about and design for performance trade-offs (latency vs. throughput vs. cost) when building ML inference systems
Strong understanding of backend service development (APIs and service reliability) as it applies to serving ML models at scale

Job Responsibility

Create, improve, and maintain production services that provide analysis for health features in collaboration with Data Scientists and MLOps Engineers
Collaborate with Data Engineers to improve ML data pipelines, tooling, and validation systems that support robust model performance
Work alongside data scientists to translate research prototypes into production ML systems optimized for scale, latency, and cost efficiency
Collaborate with researchers and product teams to align model development with health insights and member impact
Participate in on-call rotations for data science services, ensuring uptime and performance in production environments

What we offer

equity
benefits

Fulltime

New

Senior Machine Learning Engineer, Agentic

Join us in building the future of finance. Our mission is to democratize finance...

Location

United States , Bellevue; Menlo Park; New York; Washington; Denver; Westlake; Chicago; Lake Mary; Clearwater; Gainesville

Salary:

146000.00 - 220000.00 USD / Year

Robinhood

Expiration Date

Until further notice

Requirements

Strong technical expertise in software development, with understanding of agentic workflows—including reasoning loops, tool invocation, memory, and orchestration of autonomous AI agents
Hands-on experience using Large Language Models, including prompt engineering, fine-tuning, model distillation, and deploying optimized models (e.g. via DPO, PPO) into production environments
Proven ability to build and scale ML/AI systems, from experimentation to deployment—owning dataset generation, evaluation pipelines, A/B testing, and performance monitoring
Leadership and mentorship capabilities, with a track record of guiding complex technical projects and supporting the growth of teammates through code/design reviews and technical direction
Excellent communication and collaboration skills, with the ability to translate technical ideas into actionable plans and work effectively with cross-functional partners, including product and infrastructure teams
Innovation mindset and commitment to continuous learning and a bias toward action, staying at the forefront of ML/AI trends, agentic systems research, and best practices in tooling, safety, and evaluation

Job Responsibility

Design and create tools and workflows for agent development that support rapid prototyping—define agents, compose toolchains, and construct reasoning loops with minimal overhead
Build platform solutions to support scalable experimentation, synthetic dataset generation, and multi-agent evaluation across diverse tasks and domains
Develop feedback and optimization pipelines that incorporate both automated metrics and human-in-the-loop evaluation signals to fine-tune agent behavior
Implement and scale optimization techniques such as Direct Preference Optimization (DPO), Proximal Policy Optimization (PPO), and reward modeling to improve agent performance
Launch and support fine-tuned models in production environments with robust evaluation, rollback strategies, and performance monitoring
Collaborate closely with applied AI/ML teams to translate state-of-the-art research in agentic reasoning, planning, and tool use into reliable, production-ready systems

What we offer

Market competitive and pay equity-focused compensation structure
100% paid health insurance for employees with 90% coverage for dependents
Annual lifestyle wallet for personal wellness, learning and development, and more
Lifetime maximum benefit for family forming and fertility benefits
Dedicated mental health support for employees and eligible dependents
Generous time away including company holidays, paid time off, sick time, parental leave, and more
Lively office environment with catered meals, fully stocked kitchens, and geo-specific commuter benefits
Bonus opportunities
Equity

Fulltime

New

Senior Machine Learning Infrastructure Engineer

As a Senior ML Infrastructure Engineer at Plus, you will design scalable archite...

Location

United States , Santa Clara

Salary:

160000.00 - 200000.00 USD / Year

PlusAI

Expiration Date

Until further notice

Requirements

Phd or MS in Computer Science, Electrical Engineering, or related field
Good oral and written communication skills
Phd new grad or Masters with 3+ years of software engineering experience with a focus on ML infrastructure or distributed systems
Proficiency in in Python, C++, SQL
Deep understanding of containerization, orchestration technologies, distributed ML workload, and experiment tracking tools (e.g., Docker, Kubernetes, multiprocessing, Kubeflow, and mlflow)
Deploy and manage resources across multiple cloud platforms (AWS, GCP, or on-prem environments)
Proficiency in at least one deep learning framework, such as PyTorch and data pipeline tools (e.g., Apache Airflow, Prefect)
Strong knowledge of distributed systems, databases, and storage solutions
Extensive software design and development skills
Ability to learn and adapt to new technologies and contribute in a productive environment

Job Responsibility

Design and develop scalable, high-performance systems for training, inference, deploying, and monitoring ML models at scale
Build and maintain efficient data pipelines, model versioning systems, and experiment tracking frameworks
Collaborate with cross-functional teams, including ML researchers and engineers, to identify bottlenecks and improve platform usability
Implement distributed systems and storage solutions optimized for machine learning workloadsDrive improvements in CI/CD workflows for ML models and infrastructure
Ensure high availability and reliability of the ML platform by implementing robust monitoring, logging, and alerting systems
Stay current with industry trends and integrate relevant tools and frameworks to enhance the platform
Mentor junior engineers and contribute to a culture of technical excellence
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
Ensure team compliance with QMS, monitor quality, and drive process improvements

What we offer

Work, learn and grow in a highly future-oriented, innovative and dynamic field
Wide range of opportunities for personal and professional development
Catered free lunch, unlimited snacks and beverages
Highly competitive salary and benefits package, including 401(k) plan

Fulltime

New

Senior Director - Data Engineering & Machine Learning

Lead the Data Revolution at Modus Create. At Modus Create, we empower the world’...

Location

Canada

Salary:

Not provided

Modus Create

Expiration Date

Until further notice

Requirements

15+ years in data or software engineering roles
7+ years leading Data Engineering/ML teams—ideally at scale or in global consulting contexts
Hands-on experience with cloud data platforms, big data toolchains (Spark, Kafka), data transformation tools (Airflow, dbt), and ML platforms
Success in pre-sales, solutioning, and growing data/ML engagements within enterprise or mid-market accounts
Demonstrated ability to create enablement programs, uplift team capabilities, and grow inclusive, high-performing engineering cultures
Deep empathy for client pain points and the ability to craft and deliver impactful, measurable solutions
Excellent across technical, executive, and cross-functional settings, with an ability to successfully navigate diverse cultural differences

Job Responsibility

Build Modern Data Platforms
Design and oversee architecture for cloud-native data platforms, pipelines, and streaming systems on AWS, Azure, or GCP
Ensure robust solutions using platforms such as Databricks, Snowflake, Redshift, BigQuery, Spark, Kafka, Airflow, dbt, and Kubernetes
Deliver Products that are Intelligent
Define and drive responsible ML strategy, from model development to integration, using platforms like SageMaker, Azure ML, or TensorFlow
Enable smarter client experiences by embedding ML into applications, automation, and analytics
Lead & Grow Teams
Foster a culture of trust, continuous learning, and experimentation by hiring, mentoring, and empowering distributed teams of data and ML engineers
Define career paths, feedback frameworks, and learning programs grounded in a culture of experimentation,continuous growth, and a sense of belonging at every level
Shape Technical Strategy & Best Practices

What we offer

Remote work with flexible working hours
Modus Global Office Programme:for when you want to get out of your home, we offer on-demand access to private offices, meeting rooms, coworking spaces and business lounges in locations in over 120 countries
Employee Referral Program
Client Referral Program
Travel according to client or team needs
The chance to work side-by-side with thought leaders in emerging tech
Access to more than 12,000 courses with a licensed Coursera account
Possibility to obtain paid certification/courses if they align with company goals and are relevant to the employee's role

Fulltime

New

Senior Software Engineer, Machine Learning

At Machina Labs, we’re reshaping manufacturing through advanced robotics and mac...

Location

United States , Chatsworth

Salary:

155000.00 - 190000.00 USD / Year

Machina Labs

Expiration Date

Until further notice

Requirements

MS or PhD. in Data Science, Computer Science, Machine Learning, Statistics, or a related field
4+ years of hands-on experience in machine learning systems, algorithms, and applications (e.g. deep learning, time series analysis, etc.)
Experienced and very comfortable coming up with machine learning architectures and training models from scratch
Extensive Python programming experience
Familiarity with big data platforms (Hadoop, Spark, Hive) and analytics environments (Databricks, Sagemaker/Azure ML, Jupyter)
Experience in build/release systems and processes
Quick learner of new technologies and experienced in fast-paced iterative design
Strong communicator with the ability to explain complex topics to technical and non-technical audiences
Proven track record of being able to solve complex problems independently and as part of an integrated team

Job Responsibility

Identify opportunities for machine learning automation and predictive modeling by analyzing available data and collaborating with engineers and manufacturing process experts
Conduct data mining, develop model architectures, train and deploy models, and define metrics aligned with business objectives
Design, develop, and deploy ETL and data cleansing processes to extract relevant features for modeling (in collaboration with other team members)
Assist team members in data analysis and interpretation
Design and conduct experiments to test and validate solutions and models
Build a production-ready pipeline supporting multiple machine learning models
Develop monitoring tools for data quality and system performance
Provide guidance to team members and actively participate in interview processes to hire additional team members

What we offer

Medical, Dental, Vision
PTO
Stock Options

Fulltime

New

Senior Platform Engineer, ML Data Systems

We’re looking for an ML Data Engineer to evolve our eval dataset tools to meet t...

Location

United States , Mountain View

Salary:

137871.00 - 172339.00 USD / Year

Khan Academy

Expiration Date

Until further notice

Requirements

Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field
5 years of Software Engineering experience with 3+ of those years working with large ML datasets, especially those in open-source repositories such as Hugging Face
Strong programming skills in Go, Python, SQL, and at least one data pipeline framework (e.g., Airflow, Dagster, Prefect)
Experience with data versioning tools (e.g., DVC, LakeFS) and cloud storage systems
Familiarity with machine learning workflows — from training data preparation to evaluation
Familiarity with the architecture and operation of large language models, and a nuanced understanding of their capabilities and limitations
Attention to detail and an obsession with data quality and reproducibility
Motivated by the Khan Academy mission “to provide a free world-class education for anyone, anywhere.”
Proven cross-cultural competency skills demonstrating self-awareness, awareness of other, and the ability to adopt inclusive perspectives, attitudes, and behaviors to drive inclusion and belonging throughout the organization.

Job Responsibility

Evolve and maintain pipelines for transforming raw trace data into ML-ready datasets
Clean, normalize, and enrich data while preserving semantic meaning and consistency
Prepare and format datasets for human labeling, and integrate results into ML datasets
Develop and maintain scalable ETL pipelines using Airflow, DBT, Go, and Python running on GCP
Implement automated tests and validation to detect data drift or labeling inconsistencies
Collaborate with AI engineers, platform developers, and product teams to define data strategies in support of continuously improving the quality of Khan’s AI-based tutoring
Contribute to shared tools and documentation for dataset management and AI evaluation
Inform our data governance strategies for proper data retention, PII controls/scrubbing, and isolation of particularly sensitive data such as offensive test imagery.

What we offer

Competitive salaries
Ample paid time off as needed
8 pre-scheduled Wellness Days in 2026 occurring on a Monday or a Friday for a 3-day weekend boost
Remote-first culture - that caters to your time zone, with open flexibility as needed, at times
Generous parental leave
An exceptional team that trusts you and gives you the freedom to do your best
The chance to put your talents towards a deeply meaningful mission and the opportunity to work on high-impact products that are already defining the future of education
Opportunities to connect through affinity, ally, and social groups
401(k) + 4% matching & comprehensive insurance, including medical, dental, vision, and life.

Fulltime

New

Senior Machine Learning Engineer

Our Machine Learning Team is developing next-generation AI capabilities for High...

Location

Canada , Vancouver

Salary:

146000.00 - 220000.00 CAD / Year

Highspot

Expiration Date

Until further notice

Requirements

Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field
5+ years of experience in developing and deploying machine learning models and systems
Strong proficiency in at least one programming language (Python, Java, C++, etc.) and experience with machine learning libraries (TensorFlow, Keras, PyTorch, etc.)
In-depth understanding of machine learning concepts, such as supervised and unsupervised learning, deep learning, and natural language processing
Experience with data processing tools and technologies, such as Spark, Flink, Hadoop, and SQL databases
Strong problem-solving skills and ability to analyze complex data sets
Excellent communication skills and ability to articulate complex technical concepts to non-technical stakeholders
An entrepreneurial spirit: you’re agile, creative, resourceful, and tenacious as you solve problems and achieve team and company goals
Comfortable with modern open source technologies and tools
Passion to learn new technologies and infrastructure

Job Responsibility

Collaborate with product and data science teams to identify opportunities that drive customer values, and define machine learning requirements, lead the development and deployment of machine learning solutions and applications, while ensuring scalability, reliability, and maintainability
Develop and maintain a robust machine learning platform that enables the efficient deployment and management of machine learning models across our product offerings
Stay up-to-date with the latest machine learning research and trends, and apply them to our product offerings, while mentoring and collaborating with junior team members to improve their technical skills
Partner cross-functionally across all of Highspot’s feature engineering crews, as well as with QA/DevOps/Site-Reliability

What we offer

Comprehensive medical, dental, vision, disability, and life benefits
Group Retirement Savings Plan (RRSP) and matching employer contributions (DPSP) with immediate vesting
Flexible PTO
Generous Holiday Schedule + 5 Days for Annual Holiday Week
Quarterly Recharge Fridays (paid days off for mental health recharge)
Flexible work schedules
Access to Coaches and Therapists through Modern Health
2 Volunteer days per year
Monthly transportation allowance for employees that work in our Vancouver Hub location
Employees are eligible to receive stock options

Fulltime

Senior Platform Machine Learning Engineer

EarnIn

Location:
United States, Mountain View

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
December 08, 2025

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