MLOps Engineer

ML Engineer / MLOps Engineer

We are looking for professionals with 5+ years of experience in building scalabl...

Location

India , Chennai

Salary:

Not provided

InfoGrowth

Expiration Date

Until further notice

Requirements

Certified Machine Learning Specialty
Google Professional Machine Learning Engineer
Azure AI Engineer Associate
Databricks / MLflow Certifications (Good to have)

Job Responsibility

Design and build scalable data pipelines and ML infrastructure
Deploy and productionize machine learning models
Develop scalable tools for ML training and inference
Implement CI/CD pipelines and automation for ML workflows
Ensure model versioning, auditability, and data security
Support end-to-end model development and PoC deployments
Evaluate new technologies to improve system performance and reliability
Collaborate with clients to gather requirements and track progress

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

We are looking for a proactive MLOps Engineer to join our staff data engineer an...

Location

Spain

Salary:

Not provided

Bark

Expiration Date

Until further notice

Requirements

Experience deploying and maintaining Python services in a major cloud environment (AWS, GCP, Azure)
Specific experience with the AWS stack, including Kinesis, Lambdas, Glue, Firehose, and Athena
Experience with MLOps frameworks and experiment tracking tools such as AWS Sagemaker, MLFlow, Databricks, or W&B
Basic knowledge of ML Inference REST APIs (FastAPI)
Great skills improving and operating Schema Registries and Data Catalogs (Glue, Databricks, etc.)
Relevant CI/CD experience (e.g., GitHub Actions, Gitlab Pipelines) automating tests and updates in schema registries and lambda releases
Solid experience with SQL and data warehousing, data lake environments (e.g. DataBricks, BigQuery, Redshift, S3)
Familiarity with cloud observability tools (e.g. Datadog, NewRelic, or Cloudwatch)

Job Responsibility

Build and operate a scalable data platform ingesting real-time events with a high-throughput rate
Collaborate with Data Scientists to transition ML models from experimentation to production
Build and maintain ML infrastructure for model serving (using FastAPI) and track model performance and lifecycle over time
Collaborate with analysts, engineers and product managers to understand user needs and take ownership of producing new event tracking functionality
Implement automations, high data quality controls, ensure data integrity in the ingested data, and create necessary monitoring alerts

Fulltime

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

MLOps Engineer

We are seeking an experienced MLOps Engineer to design, deploy, monitor, and mai...

Location

United States , Houston

Salary:

Not provided

Robert Half

Expiration Date

Until further notice

Requirements

Master’s degree or higher (PhD preferred) in Computer Science, Engineering, or related discipline
5+ years of relevant experience in MLOps, ML engineering, platform engineering, or DevOps
Strong hands-on experience with AWS, Microsoft Azure, and Snowflake
Proficiency in Python and SQL
Proven experience deploying and managing ML models in production environments
Experience with AWS SageMaker and Azure Machine Learning
Experience building and integrating data pipelines with Snowflake
Strong understanding of CI/CD pipelines, infrastructure automation, and model versioning
Experience with containers and orchestration tools such as Docker and Kubernetes
Experience with Airflow, Azure Data Factory, or similar workflow orchestrators

Job Responsibility

Design and implement end-to-end ML pipelines for ingestion, feature engineering, training, validation, deployment, and monitoring
Deploy and manage ML models in production across AWS, Azure, and Snowflake ecosystems
Build batch and real-time inference pipelines using cloud-native and platform-native services
Automate model packaging, testing, releases, and rollback using CI/CD best practices
Integrate ML workflows with AWS SageMaker, AWS Lambda, Azure Machine Learning, Azure Data Factory, and Snowflake
Build and maintain orchestration workflows using Airflow, Azure Data Factory, or similar tools
Implement experiment tracking, model registries, and model governance processes
Monitor model accuracy, drift, latency, throughput, pipeline performance, and infrastructure usage
Establish advanced deployment strategies (canary, shadow, blue-green, rollback)
Collaborate with cross-functional teams to transition models from research to production

What we offer

medical
vision
dental
life and disability insurance
401(k) plan

Middle MLOps Engineer

Vention is a global engineering partner to tech leaders and fast-growing startup...

Location

Poland , Gdansk

Salary:

8000.00 PLN / Month

Vention

Expiration Date

Until further notice

Requirements

Experience in cloud platform engineering, DevOps, MLOps, or a similar field
Expertise in cloud platforms (e.g., Microsoft Azure), containerization technologies (Docker, Kubernetes), and CI/CD tools (ArgoCD, Azure DevOps, Helm)
Experience building ML infrastructure and familiarity with machine learning concepts
Ability to design scalable, secure, and efficient cloud systems, and familiarity with security and compliance standards in enterprise-grade cloud environments
Proficiency in Python programming and familiarity with LLM/MLOps best practices
Genuine drive to learn emerging paradigms and best practices in generative AI and agentic AI
A passion for collaboration, problem-solving, and fostering a culture of continuous improvement

Job Responsibility

Collaborate with multiple product teams to implement Security, Data Protection and MLOps strategies that fuel business growth and ensure High Availability for AI/ML workloads
Implement and manage Continuous Deployment (CD) pipelines using tools such as ArgoCD and Helm
Ensure compliance with security standards and architect and deploy scalable enterprise-grade cloud infrastructure for ML workloads using industry standard tools like Kubernetes
Develop and maintain Infrastructure as Code (IaC) using tools like Terraform
Implement robust model performance, cost, drift monitoring, and logging practices with tools like Prometheus, Langfuse, etc.
Build and automate end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring
Champion MLOps best practices across the organization, mentoring and training stakeholders on tools and methodologies

What we offer

EDU corporate community (300+ members): tech communities, interest clubs, events, a small R&D lab, a knowledge base, and a dedicated AI track
Licenses for AI tools: GitHub Copilot, Cursor, and others
Private medical care with LuxMed
Kafeteria MyBenefit credits for stores, restaurants, and cafés
Access to a Multisport membership to stay active
Glasses reimbursement program
Referral bonuses for bringing in new talent

Fulltime

Middle MLOps Engineer

Join our award-winning DevOps practice, recognized as "Best DevOps Services" at ...

Location

Poland , Wroclaw

Salary:

8000.00 PLN / Month

Vention

Expiration Date

Until further notice

Requirements

Experience in cloud platform engineering, DevOps, MLOps, or a similar field
Expertise in cloud platforms (e.g., Microsoft Azure), containerization technologies (Docker, Kubernetes), and CI/CD tools (ArgoCD, Azure DevOps, Helm)
Experience building ML infrastructure and familiarity with machine learning concepts
Ability to design scalable, secure, and efficient cloud systems, and familiarity with security and compliance standards in enterprise-grade cloud environments
Proficiency in Python programming and familiarity with LLM/MLOps best practices
Genuine drive to learn emerging paradigms and best practices in generative AI and agentic AI
A passion for collaboration, problem-solving, and fostering a culture of continuous improvement

Job Responsibility

Collaborate with multiple product teams to implement Security, Data Protection and MLOps strategies that fuel business growth and ensure High Availability for AI/ML workloads
Implement and manage Continuous Deployment (CD) pipelines using tools such as ArgoCD and Helm
Ensure compliance with security standards and architect and deploy scalable enterprise-grade cloud infrastructure for ML workloads using industry standard tools like Kubernetes
Develop and maintain Infrastructure as Code (IaC) using tools like Terraform
Implement robust model performance, cost, drift monitoring, and logging practices with tools like Prometheus, Langfuse, etc.
Build and automate end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring
Champion MLOps best practices across the organization, mentoring and training stakeholders on tools and methodologies

What we offer

EDU corporate community (300+ members): tech communities, interest clubs, events, a small R&D lab, a knowledge base, and a dedicated AI track
Licenses for AI tools: GitHub Copilot, Cursor, and others
Private medical care with LuxMed
Kafeteria MyBenefit credits for stores, restaurants, and cafés
Access to a Multisport membership to stay active
Glasses reimbursement program
Referral bonuses for bringing in new talent

Fulltime

Middle MLOps Engineer

Join our award-winning DevOps practice, recognized as "Best DevOps Services" at ...

Location

Poland , Lodz

Salary:

8000.00 PLN / Month

Vention

Expiration Date

Until further notice

Requirements

Experience in cloud platform engineering, DevOps, MLOps, or a similar field
Expertise in cloud platforms (e.g., Microsoft Azure), containerization technologies (Docker, Kubernetes), and CI/CD tools (ArgoCD, Azure DevOps, Helm)
Experience building ML infrastructure and familiarity with machine learning concepts
Ability to design scalable, secure, and efficient cloud systems, and familiarity with security and compliance standards in enterprise-grade cloud environments
Proficiency in Python programming and familiarity with LLM/MLOps best practices
Genuine drive to learn emerging paradigms and best practices in generative AI and agentic AI
A passion for collaboration, problem-solving, and fostering a culture of continuous improvement

Job Responsibility

Collaborate with multiple product teams to implement Security, Data Protection and MLOps strategies that fuel business growth and ensure High Availability for AI/ML workloads
Implement and manage Continuous Deployment (CD) pipelines using tools such as ArgoCD and Helm
Ensure compliance with security standards and architect and deploy scalable enterprise-grade cloud infrastructure for ML workloads using industry standard tools like Kubernetes
Develop and maintain Infrastructure as Code (IaC) using tools like Terraform
Implement robust model performance, cost, drift monitoring, and logging practices with tools like Prometheus, Langfuse, etc.
Build and automate end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring
Champion MLOps best practices across the organization, mentoring and training stakeholders on tools and methodologies

What we offer

EDU corporate community (300+ members): tech communities, interest clubs, events, a small R&D lab, a knowledge base, and a dedicated AI track
Licenses for AI tools: GitHub Copilot, Cursor, and others
Private medical care with LuxMed
Kafeteria MyBenefit credits for stores, restaurants, and cafés
Access to a Multisport membership to stay active
Glasses reimbursement program
Referral bonuses for bringing in new talent

Fulltime

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MLOps Engineer - Implementation

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MLOps Engineer - Implementation

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