Machine Learning Ops Engineer Job at Whitehall Resources Ltd (London)

Machine Learning Engineer II - Training

As a Machine Learning Engineer II on our Training team, you will develop algorit...

Location

United States , Boston

Salary:

125000.00 - 170000.00 USD / Year

Whoop

Expiration Date

Until further notice

Requirements

Bachelor's Degree in Mathematics, Statistics, Computer Science, or a related field
2+ years of ML engineering, applied research, or a similar role
2+ years experience applying advanced mathematical and statistical techniques
Experience deploying and maintaining production ML systems on cloud platforms (e.g., Kubernetes, AWS, GCP)
Familiarity with MLOps best practices and the ability to collaborate effectively with infrastructure teams on Docker, CI/CD workflows, model versioning, and observability tools
Proficiency in scientific Python and SQL
Excellent verbal and written communication skills

Job Responsibility

Design, train, and optimize machine learning algorithms for movement, exercise and training applications across diverse backend platforms
Collaborate closely with data scientists, ML Ops and software engineering teams to ensure reliable deployment, observability, and robust integration with the WHOOP ecosystem
Contribute to technical roadmap development and architectural decision-making for projects that you are involved in
Work closely with a team of data scientists in developing algorithms that power member-facing features
Work with Data Engineers to improve data pipelining, tooling for machine learning, and systems for quality and validation
Periodically serve as the on-call data scientist to respond in real time to incidents affecting production services

What we offer

equity
benefits

Fulltime

Staff Machine Learning Engineer

Machine Learning Engineers at Rocket Money further our mission by building produ...

Location

United States , San Francisco; Washington, D.C.; New York City; Silver Spring; Miami; Denver

Salary:

210000.00 - 260000.00 USD / Year

Truebill

Expiration Date

Until further notice

Requirements

8+ years of professional experience in machine learning engineering or data science roles
Proven track record of designing and implementing ML systems at consumer tech scale and speed
Extensive hands-on experience integrating ML and AI methods into production workflows, including creating evaluation tooling and effective user feedback mechanisms
Experience with prompt engineering and management, creating robust systems for testing and optimizing LLM-based applications
Expert-level proficiency in Python, SQL, and at least a handful of common ML frameworks
Understanding of ML methods at a fundamental level
Master at taking ambiguous problems, creating clarity, and breaking down work into manageable chunks for implementation
Owned the development, launch, and maintenance for several scaled ML/AI powered product experiences
Understand basic software engineering and computer science fundamentals and have applied them at consumer grade scale to build ML powered products in production environments
Technical leader who can identify both emergent technical opportunities and gaps relative to best practice

Job Responsibility

Lead the architecture and development of complex AI and ML powered features across Rocket Money's product suite
Design, implement, and maintain robust evaluation frameworks
Develop novel new product experiences
Own end to end development and implementation of ML and AI product features in collaboration with cross-functional product development teams
Provide technical mentorship

What we offer

Health, Dental & Vision Plans
Competitive Pay
401k Matching
Unlimited PTO
Lunch daily (in-office only)
Snacks & Coffee (in-office only)
Commuter benefits (in-office only)
Bonus

Fulltime

Engineering Manager - Machine Learning Infrastructure

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

241200.00 - 400000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

8–10 years of experience in ML infrastructure, including direct hands-on expertise as an engineer, IC/TL
2+ years of experience managing infrastructure or ML platform engineers
Proven experience delivering and operating ML or AI infrastructure at scale
Solid technical depth across ML/AI infrastructure domains (e.g., feature stores, pipelines, deployment, inference, observability)
Demonstrated ability to drive execution on complex technical projects with cross-team stakeholders
Strong communication and stakeholder management skills

Job Responsibility

Lead and support the ML Infra team, driving project execution and ensuring delivery on key commitments
Build and launch Plaid’s next-generation feature store to improve reliability and velocity of model development
Define and drive adoption of an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines, deployment tooling, and inference systems
Partner with ML product teams to understand requirements and deliver solutions that accelerate model development and iteration
Recruit, mentor, and develop engineers, fostering a collaborative and high-performing team culture

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

Staff Machine Learning Engineer

Machine learning is the crucial enabler for every financial service EarnIn provi...

Location

United States , Mountain View

Salary:

272700.00 - 333300.00 USD / Year

EarnIn

Expiration Date

Until further notice

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field, or relevant equivalent experience
7+ years of industry machine learning experience and excellent software engineering skills
Strong programming skills in Python, with familiarity in ML frameworks such as TensorFlow or PyTorch
Experience with ML cloud platforms like AWS Sagemaker, Databricks, or GCP Vertex AI
Experience with LLM Ops, foundation model APIs, and AI engineering
Familiarity with data pipeline and workflow management tools
Strong communication and collaboration skills
Passion for learning and staying updated with the latest machine learning and platform engineering industry trends

Job Responsibility

Design, build, and maintain the ML and AI platform and tools to support the end-to-end machine learning lifecycle
Work closely with other machine learning engineers to understand their workflows, optimize model training and deployment processes, and ensure the reproducibility of results
Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform
Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities
Set examples of outstanding operational excellence. Be the catalyst for step-jump changes
Be a mentor, coach, leader and inspiration to those around you

What we offer

equity and benefits

Fulltime

Senior Platform Machine Learning Engineer

Machine learning is the crucial enabler for every financial service EarnIn provi...

Location

United States , Mountain View

Salary:

232200.00 - 283800.00 USD / Year

EarnIn

Expiration Date

Until further notice

Requirements

Bachelor's or Master’s degree in Computer Science, Engineering, or a related field, or relevant equivalent experience
4+ years of industry machine learning experience and excellent software engineering skills
Strong programming skills in Python, with familiarity in ML frameworks such as TensorFlow or PyTorch
Experience with ML cloud platforms like AWS Sagemaker, Databricks, or GCP Vertex AI
Experience with LLM Ops, foundation model APIs, and AI engineering
Familiarity with data pipeline and workflow management tools
Strong communication and collaboration skills
Passion for learning and staying updated with the latest machine learning and platform engineering industry trends

Job Responsibility

Design, build, and maintain the ML and AI platform and tools to support the end-to-end machine learning lifecycle
Work closely with other machine learning engineers to understand their workflows, optimize model training and deployment processes, and ensure the reproducibility of results
Ensure scalability, reliability, cost efficiency, and ease of use of the machine learning platform
Contribute to evaluating and adopting new technologies and tools to enhance our machine-learning capabilities
Set examples of outstanding operational excellence. Be the catalyst for step-jump changes

What we offer

equity and benefits

Fulltime