Senior ML Operations Engineer Jobs

New

Senior Software Engineer - ML Infrastructure

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

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

5+ years of industry experience as a software engineer, with strong focus on ML/AI infrastructure or large-scale distributed systems
Hands-on expertise in building and operating ML platforms (e.g., feature stores, data pipelines, training/inference frameworks)
Proven experience delivering reliable and scalable infrastructure in production
Solid understanding of ML Ops concepts and tooling, as well as best practices for observability, security, and reliability
Strong communication skills and ability to collaborate across teams

Job Responsibility

Design and implement large-scale ML infrastructure, including feature stores, pipelines, deployment tooling, and inference systems
Drive the rollout of Plaid’s next-generation feature store to improve reliability and velocity of model development
Help define and evangelize an ML Ops “golden path” for secure, scalable model training, deployment, and monitoring
Ensure operational excellence of ML pipelines and services, including reliability, scalability, performance, and cost efficiency
Collaborate with ML product teams to understand requirements and deliver solutions that accelerate experimentation and iteration
Contribute to technical strategy and architecture discussions within the team
Mentor and support other engineers through code reviews, design discussions, and technical guidance

What we offer

medical, dental, vision, and 401(k)

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

Senior Support and Operations Engineer

Senior Support and Operations Engineer to join Data Management team, taking owne...

Location

Greece , Athens

Salary:

Not provided

Metlen Group

Expiration Date

Until further notice

Requirements

BSc or MSc in Computer Science or related technical field
+4 years of experience in Operations or IT roles (Data Engineering, ML Engineering, Software Engineering, or similar)
Experience in system monitoring, technical support, and incident handling
Hands-on experience with Cloud platforms
Practical exposure to MLOps and DevOps frameworks (Azure DevOps/MLOps, Docker, Kubernetes, AWS DevOps/MLOps)
Experience managing CI/CD pipelines, especially in Azure is considered a plus
Experience with GitHub is an advantage
Solid hands-on experience in SQL and Python
Experience managing enterprise-scale Data/ML workflows
Strong analytical and problem-solving abilities

Job Responsibility

Oversee and optimize DevOps and MLOps operations for model deployment, monitoring, and automation
Execute, maintain, and improve CI/CD pipelines for Data Engineering and ML deployments
Collaborate closely with Data Engineers to strengthen deployment processes and operational efficiency
Monitor, troubleshoot, and ensure smooth execution of daily Corporate Data Warehouse workflows
Handle technical support requests efficiently, ensuring SLA compliance
Maintain high system availability and reliability through proactive monitoring
Implement minor enhancements, bug fixes, and performance optimizations
Apply version control best practices and ensure proper deployment governance
Collaborate cross-functionally to streamline deployment processes across environments
Identify opportunities for automation, observability, and improved monitoring

What we offer

Competitive remuneration package
Ticket Restaurant Card
Group Health Insurance Plan
Preferential Protergia household energy plan
Pension Plan

Fulltime

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 Software Engineer - Network Enablement (Applied ML)

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

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong software engineering skills including systems design, APIs, and building reliable backend services (Go or Python preferred)
Production experience with batch and streaming data pipelines and orchestration tools such as Airflow or Spark
Experience building or operating real-time scoring and online feature-serving systems, including feature stores and low-latency model inference
Experience integrating model outputs into product flows (APIs, feature flags) and measuring impact through experiments and product metrics
Experience with model lifecycle and operations: model registries, CI/CD for models, reproducible training, offline & online parity, monitoring and incident response

Job Responsibility

Embed model inference into Network Enablement product flows and decision logic (APIs, feature flags, backend flows)
Define and instrument product + ML success metrics (fraud reduction, retention lift, false positives, downstream impact)
Design and run experiments and rollout plans (backtesting, shadow scoring, A/B tests, feature-flagged releases) to validate product hypotheses
Build and operate offline training pipelines and production batch scoring for bank intelligence products
Ship and maintain online feature serving and low-latency model inference endpoints for real-time partner/bank scoring
Implement model CI/CD, model/version registry, and safe rollout/rollback strategies
Monitor model/data health: drift/regression detection, model-quality dashboards, alerts, and SLOs targeted to partner product needs
Ensure offline and online parity, data lineage, and automated validation / data contracts to reduce regressions
Optimize inference performance and cost for real-time scoring (batching, caching, runtime selection)
Ensure fairness, explainability and PII-aware handling for partner-facing ML features

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

New

Senior Engineering Manager - Risk

Our mission is to build the intelligent, automated systems and operational tools...

Location

United States; Canada , San Francisco; New York; Portland

Salary:

239000.00 - 298800.00 USD / Year

Mercury

Expiration Date

Until further notice

Requirements

9+ years of software development experience
3–5+ years of engineering management in a high-scale tech environment
AI/ML expertise—you’ve built and launched applied AI products (from LLMs to traditional ML models), shipping them from 0→1 and scaling 1→10 in production environments
Proven success building large-scale backend distributed systems, ideally involving integrations and decision automation
Experience with or curiosity about KYC, AML, risk, or compliance systems in financial services or fintech
A track record of raising the bar for quality and reliability, balancing shipping speed with technical excellence
Strong communication and leadership skills—you can inspire engineers, partner across functions, and adapt your management style to the moment
The ability to hire, retain, and develop exceptional technical talent
A pragmatic builder’s mindset: you believe beautiful systems are those that work, adapt, and last

Job Responsibility

Lead teams (4–8 engineers each) responsible for account onboarding, KYC/KYB, AML, and fraud detection decisioning and workflows, and operational tooling
Apply AI/ML—from traditional models to large language models—to unlock faster, real-time bank account application approvals. This work sits on the critical business path, directly driving efficiency and revenue growth
Partner with Product, Risk, and Data teams to design and deliver scalable systems that balance user experience with compliance rigor
Shape the next generation of our KYC and risk platforms—reliable, resilient, and easy to extend as regulations and business needs evolve
Create a strong culture of operational excellence, with measurable improvements to uptime, accuracy, and system quality
Build, mentor, and grow engineering talent
help managers and senior engineers level up technically and organizationally
Drive clarity amid complexity: translating between regulatory nuance and technical execution
Foster collaboration across teams to align on priorities, simplify interfaces, and make the whole system more maintainable and elegant

What we offer

base salary
equity
benefits

Fulltime

Senior Data Engineer

Fospha is dedicated to building the world's most powerful measurement solution f...

Location

India , Mumbai

Salary:

Not provided

Blenheim Chalcot

Expiration Date

Until further notice

Requirements

Excellent knowledge of PostgreSQL and SQL technologies
Fluent in Python
Understanding of data architecture, pipelines and ELT flows/ technology/ methodologies
Understanding of agile methodologies and practices
Bachelor's or Master's degree in Computer Science, Engineering, or a related field

Job Responsibility

Implement and maintain ELT (Extract, Load, Transform) processes using scalable data pipelines and data architecture
Collaborate with cross-functional teams to understand data requirements and deliver effective solutions
Ensure data integrity and quality across various data sources
Support data-driven decision-making by providing clean, reliable, and timely data
Define the standards for high-quality data for Data Science and Analytics use-cases and help shape the data roadmap for the domain
Design, develop, and maintain the data models used by ML Engineers, Data Analysts and Data Scientists to access data
Conduct exploratory data analysis to uncover data patterns and trends
Identify opportunities for process improvement and drive continuous improvement in data operations
Stay updated on industry trends, technologies, and best practices in data engineering

What we offer

Competitive salary
Be part of a leading global venture builder, Blenheim Chalcot, and learn from the incredible talent in BC
Be exposed to the right mix of challenges and learning and development opportunities
Flexible Benefits including Private Medical and Dental, Gym Subsidiaries, Life Assurance, Pension scheme etc.
25 days of paid holiday + your birthday off
Free snacks in the office
Quarterly team socials

Fulltime

New

Senior Engineering Manager, Computer Vision

Hover helps people design, improve, and protect the properties they love. With p...

Location

United States , San Francisco/New York

Salary:

247000.00 - 305000.00 USD / Year

HOVER

Expiration Date

Until further notice

Requirements

2+ years of managing high impact CV/ML teams (or tech lead / staff+ leadership) with a track record of building high-performing teams
5+ years of hands-on experience in computer vision or ML (ideally 3D reconstruction, multi-view geometry, or ML-based reconstruction)
Proven track record partnering with product teams to scope features, run experiments, and iterate based on customer feedback and data
Familiarity with modern MLOps stacks (cloud GPUs, CI/CD, monitoring) and a passion for measurable reliability and cost control
Ability to articulate complex trade-offs to executives, engineers, and customers alike
Bachelor’s, Master’s, or PhD in CS, ML, or related field

Job Responsibility

Leading the Team: Build and nurture a high-performing, diverse team of senior ICs and emerging leaders. From hiring and onboarding to coaching and career-pathing, you’ll make talent development your first priority
Owning a Scaling Product Line: Take end-to-end ownership of a critical computer vision product area, ensuring our research breakthroughs translate into production systems that delight customers at scale
Shaping the Roadmap: Partner with Product and Design to translate market opportunities and research advances into a sequenced plan. You’ll balance innovation with operational excellence, driving projects from data strategy and experimentation through to reliable production deployment
Driving Technical Excellence: Set engineering standards for accuracy, latency, cost control, and reliability. Model strong cross-functional collaboration and ensure your team’s work integrates smoothly into Hover’s larger platform
Communicating Impact: Clearly articulate progress, trade-offs, and technical choices to executives, stakeholders, and the broader team
earning trust at every level

What we offer

Compensation - Competitive salary and meaningful equity in a fast-growing company
Healthcare - Comprehensive medical, dental, and vision coverage for you and dependents
Paid Time Off - Unlimited and flexible vacation policy
Paid Family Leave - We support work/life balance and offer generous paid parental and new child bonding leave
Mandatory Self-Care Days - A day set aside each month to allow employees to recharge
Remote Wellbeing Resources - We provide recurring fitness classes, meditation/ mindfulness tools, virtual therapy, and family planning assistance
Learning - We encourage continued education and will help cover the cost of management training, conferences, workshops, or certifications

Fulltime

Senior ML Operations Engineer

Whoop

Location:
United States, Boston

Category:
IT - Software Development

Contract Type:
Not provided

Salary:

Job Description:

Job Responsibility:

Requirements:

Additional Information:

Job Posted:
December 13, 2025

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