Senior MLOps Engineer Job at NorthBay

Senior MLOps Engineer

We're looking for an MLOps Engineer to help ensure our machine learning models r...

Location

Denmark , København

Salary:

Not provided

Life Science Talent

Expiration Date

Until further notice

Requirements

Experience deploying machine learning models into production and managing their lifecycle
Experience implementing model governance, including versioning, monitoring, drift detection, and reporting
Familiarity with MLOps tools such as MLflow, Kubeflow, or DVC
Solid understanding of CI/CD systems (e.g., GitHub Actions, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm)
Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing
Experience mentoring or supporting colleagues to help them grow their technical skills
Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role
Strong proficiency in Python
Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes)
Ability to design scalable, secure, and observable systems in fast-moving environments

Job Responsibility

Own and manage the full lifecycle of both ML models and core infrastructure – from development and deployment to monitoring and continuous improvement
Build and maintain robust CI/CD pipelines for both software and ML workflows
Ensure reliability, scalability, observability, and security of production systems and ML infrastructure
Automate deployment, orchestration, and environment management using modern DevOps tooling
Collaborate closely with software engineers, ML engineers, and product teams to bring ML-powered features to production
Proactively detect, troubleshoot, and resolve infrastructure and model performance issues
Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering
Document infrastructure, workflows, and operational procedures clearly and thoroughly

What we offer

Equipment provided by Corti

Fulltime

Senior MLOps Engineer

Prolific is not just another player in the AI space – we are the architects of t...

Location

United Kingdom

Salary:

Not provided

Prolific

Expiration Date

Until further notice

Requirements

5+ years experience with cloud infrastructure and infrastructure as code
Previous experience with the ML and LLM lifecycle - training, hosting, optimisation, observability
Used to working closely with researchers and data scientists - taking experiments from worksheets into production
Strong grasp of ML fundamentals and modern GenAI stack

Job Responsibility

Infrastructure & Platform Engineering: Design and maintain scalable cloud environments (GCP/AWS) using Terraform
Manage GPU/TPU resource allocation for training, fine-tuning, and interactive notebooks
Build internal services and CLI tools to streamline the developer experience for the AI team
ML & LLM Orchestration: Design CI/CD/CT (Continuous Training) pipelines using tools such as GitHub Actions, MLFlow, Vertex AI Pipelines
Develop reusable patterns for model serving
Managing service deployments to Kubernetes
Manage and optimize vector databases and embedding pipelines for RAG-based systems
Performance & Optimization: Implement techniques to reduce latency and increase throughput
Solve scaling bottlenecks for serverless or containerized model deployments
Optimize GPU utilization and cloud spend without compromising performance

What we offer

competitive salary
benefits
remote working
impactful, mission-driven culture

Senior MLOps Engineer

A fast-growing, VC-backed AI company is seeking a Senior MLOps Engineer to help ...

Location

United States

Salary:

Not provided

Orbis Consultants

Expiration Date

Until further notice

Requirements

4+ years of experience in MLOps with hands-on ownership of production ML systems
Degree in Computer Science or a related field (Bachelor’s or Master’s)
Strong expertise in Python and ML libraries (TensorFlow, PyTorch, or similar)
Experience with ML lifecycle management tools
Practical experience deploying and monitoring deep learning models
Proficiency with cloud platforms (AWS, Azure, or GCP)

Job Responsibility

Design, build, and maintain infrastructure for deploying, monitoring, and updating ML models in production
Automate end-to-end pipelines covering ingestion, preprocessing, training, validation, and deployment
Implement monitoring for model performance, drift, latency, and accuracy
Ensure ML systems are secure, scalable, and cost-efficient
Partner with ML engineers, data scientists, and product teams to move models seamlessly from research to production
Apply software engineering best practices—including CI/CD, testing, and version control—to ML workflows
Continuously improve documentation, tooling, and infrastructure

What we offer

great equity and the chance to join a rocketship

Fulltime

Senior MLOps Engineer

If you’re passionate about scalability, automated deployment, and well-optimized...

Location

Romania , Bucharest

Salary:

Not provided

IT Genetics Romania

Expiration Date

Until further notice

Requirements

University degree, preferably in engineering (software, industrial, mechanical, process) or a related field
Over 5 years of experience in MLOps or machine learning engineering, with a focus on deploying and managing deep learning models at scale
Strong skills in Python, CI/CD pipelines, and ML frameworks (e.g., PyTorch, TensorFlow, OpenCV) for automating and scaling ML workflows
Expertise in monitoring and alert automation for ML workflows, including data pipelines, training processes, and model performance (e.g., Prometheus, Grafana)
Familiarity with distributed training techniques, multi-GPU strategies, and hardware optimization for deep learning
Strong communication and interpersonal skills

Job Responsibility

Design end-to-end architecture for the automated training of ML models
Create data pipelines to build relevant datasets and data annotation flows
Monitor ML model performance and data drift
Handle versioning, deployment, and integration with the software team
Develop and manage CI/CD pipelines for building, testing, and deploying models
Apply best practices for model versioning, rollback, and A/B testing to ensure reliable and accurate production releases
Set up a robust monitoring system and develop automated alerting solutions to proactively identify issues in data pipelines, model training, validation, and data variation
Promote MLOps best practices (Infrastructure as Code, reproducibility, security) and continuously improve internal processes to increase reliability and efficiency
Research and implement cutting-edge technologies to improve training efficiency (e.g., distributed training, HPC, multi-GPU strategies) for the research team
Explore future MLOps frameworks and GPU-based cloud solutions as part of the scalability roadmap

What we offer

Meal tickets
A place where your voice truly matters
Performance bonuses
A day off on your birthday
Private medical subscription
Trainings and learning resources
Hybrid work model
Bookster subscription
A friendly, passionate, and solution-oriented team
Opportunities to grow or change your role within the company

Senior MLOps Engineer

As an MLOps Engineer in DAMO service line, you will be responsible for ensuring ...

Location

Singapore , Singapore

Salary:

Not provided

Thoughtworks

Expiration Date

Until further notice

Requirements

High proficiency in Python (Pandas, NumPy, Scikit-learn) for scripting, analysis, and maintaining production models
Strong SQL skills for querying, data manipulation, and operational data checks
Experience building or maintaining GenAI / agentic solutions (e.g., RAG, LlamaIndex, CrewAI, or similar orchestration/RAG tooling)
Solid understanding of classical ML algorithms, model evaluation, and challenges like drift and bias
Hands-on experience with model monitoring (data quality, prediction quality, latency) using Prometheus, Grafana, or cloud-native tools
Experience with Azure (Databricks, Azure Machine Learning, etc.) for deployment and resource management
Familiarity with Agile methodologies (Scrum/Kanban)
Must be Singaporean citizens or already hold Singaporean Permanent Residency (PR) at the time of application
Willingness to be part of a 24x7 on-call rotation, as needed

Job Responsibility

Design, implement and maintain monitoring and alerting for ML and AI operational signals
Build and operate robust evaluation and testing pipelines for all ML and AI systems
Investigate and resolve production issues related to model behaviour
Collaborate with infrastructure and platform teams to ensure stable, performant and cost-efficient AI inference
Manage the lifecycle of ML models, prompts, embeddings, vector indices and associated components
Design and operate effective feedback loops that incorporate real user interactions
Uphold governance, safety and compliance standards
Maintain clear, comprehensive documentation
Communicate system health, risks, upcoming changes and operational insights clearly
Support the growth and development of junior team members

What we offer

Learning & Development
Interactive tools
Numerous development programs
Teammates who want to help you grow

Fulltime

Senior MLOps Engineer

This is a rare opportunity to build the foundational infrastructure that powers ...

Location

United States; United Kingdom , Palo Alto; London

Salary:

187500.00 - 395000.00 USD / Year

Luma AI

Expiration Date

Until further notice

Requirements

5+ years of professional engineering experience with deep, hands-on proficiency in Python and complex distributed systems architecture
Extensive, practical experience building and managing systems at scale, specifically with queues, scheduling, traffic-control, and fleet management
Deep expertise in our core infrastructure stack: Linux, Docker, and Kubernetes
Strong experience with Redis, S3-compatible storage, and public cloud platforms (AWS)

Job Responsibility

Architect end-to-end model serving pipelines and integrate new model architectures from our research team into our core, high-throughput inference engine
Build robust and sophisticated scheduling systems to manage jobs based on cluster availability and user priority, ensuring we optimally leverage thousands of expensive GPU resources
Design and implement dynamic, traffic-based systems for hotswapping models on our GPU workers to maximize fleet efficiency and meet product SLOs
Own the end-to-end CI/CD pipelines, including creating a resilient artifact store to manage all model checkpoints across multiple versions and providers
Develop and maintain user-friendly APIs and interaction patterns that empower our product and research teams to ship groundbreaking features at high velocity
Manage and optimize our complex inference workloads at scale, operating across multiple clusters and hardware providers

Fulltime

Senior MLOps Engineer - Data Ingestion - Paris

We are looking for a Senior MLOps Engineer to join the Panda Team (Data & ML Ope...

Location

France , Paris

Salary:

Not provided

Doctolib

Expiration Date

Until further notice

Requirements

You have at least 7+ years as an MLOps Engineer or ML Platform Engineer with proven production model lifecycle management experience
You have expert-level experience with ML orchestration tools (MLflow, Braintrust, or similar) for batch processing and inference pipelines
You have a strong Site Reliability Engineering (SRE) foundation with focus on operations excellence, reliability, and observability
You have expertise in Python for automation and ML pipeline scripting
You have strong proficiency with infrastructure-as-code tools such as Terraform and container orchestration (Kubernetes)
You have experience with model evaluation frameworks and golden dataset management
You have a solid understanding of cloud infrastructure (preferably GCP, AWS, or Azure)
You have excellent problem-solving skills with focus on identifying and resolving infrastructure bottlenecks
You are fluent in English

Job Responsibility

Design and implement end-to-end ML model pipelines in production (LLM and custom models) with robust deployment, evaluation, and monitoring frameworks
Own data pseudo-anonymization architecture within ingestion services, converting Tier 0 (personal identifiers) to Tier 1 (anonymized data) while ensuring data quality and model performance
Build and maintain secure data export services with ML-based threat detection to prevent attack vectors (SQL injection, etc.) using adaptive models rather than manual rules
Manage golden datasets and implement production model evaluation frameworks to ensure anonymization quality and system reliability
Build and maintain data pipelines that efficiently extract, transform, and load data from various sources, handling multiple data formats (text, images, audio, video)
Implement automation and orchestration tools using ML orchestration platforms (MLflow, Braintrust, or similar) to streamline infrastructure provisioning and reduce manual effort
Monitor data and ML platforms for performance, reliability, and security
identify and troubleshoot issues proactively
Mentor team members on MLOps expertise and best practices to reduce knowledge silos and build organizational capability

What we offer

Free comprehensive health insurance for you and your children
25 days of paid vacation per year, plus up to 14 days of RTT
Free mental health and coaching services through our partner Moka.care
Work from abroad for up to 10 days per year thanks to our flexibility days policy
Lunch vouchers (Swile card) worth €8.50 per working day, with €4.50 covered by Doctolib
A subsidy from the work council to refund part of the membership to a sport club or a creative class
50% reimbursement of your public transport subscription
Parent Care Program: receive one additional month of leave on top of the legal parental leave
For caregivers and workers with disabilities, a package including an adaptation of the remote policy, extra days off for medical reasons, and psychological support
Relocation support in case of international mobility

Fulltime

Senior MLOps / LLMOps Engineer

Location

Germany , Berlin

Salary:

Not provided

ImmoScout24 GmbH

Expiration Date

Until further notice

Requirements

Strong experience in MLOps (CI/CD, Docker, Kubernetes) and operating production-grade systems
Proficiency in Python and solid software engineering and scalable system design skills
Hands-on experience with LLMs and generative AI technologies (e.g. GPT, Gemini or Anthropic-like models)
Expertise in prompt engineering, agent orchestration, context management, and output validation
Experience with LLM evaluation frameworks and deploying self-hosted LLMs
Familiarity with cloud platforms (e.g. AWS, GCP) as well as DevOps, testing, and observability practices
Strong communication skills and ability to collaborate with cross-functional teams and stakeholders

Job Responsibility

Design and maintain scalable ML/LLM infrastructure and pipelines
Productionize traditional ML and generative AI solutions with cross-functional product teams
Own the ML/LLMOps lifecycle: prompting, deployment, monitoring, evaluation and optimization
Build and evolve an LLM Gateway service to standardize access, routing, and governance
Develop evaluation frameworks to measure quality, performance, and reliability of LLM outputs
Design and implement MCP-compatible services to enable standardized context exchange between LLMs, tools, and data sources
Integrate MCP into internal platforms to support tool use, retrieval, and agent-based workflows across teams
Work with AWS and integrate self-hosted open-source AI models for scalable, secure applications
Ensure observability, cost efficiency, and system performance
Contribute to project management, stakeholder communication and cross-team collaboration

What we offer

A competitive salary package and a bonus on top
Hybrid work model with three days of on-site work per week in the office
30 days of vacation per year
Possibility to work from abroad for 10 days per year
Relocation agency support with visa process and attractive relocation package
Plus membership for tenants on ImmoScout24
Dedicated learning time per month, online courses on ScoutAcademy, regular book challenges, structured feedback, Lunch & Learn events and individual career paths
Professional family service for childcare
Bring your dog to work (upon approval)
Subsidized public transport or Job Bikes

Select Country

Senior MLOps Engineer

Job Description

Job Responsibility

Requirements

Nice to have

What we offer

Looking for more opportunities?

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer

Senior MLOps Engineer - Data Ingestion - Paris

Senior MLOps / LLMOps Engineer

Our AI answers in your language