Senior MLOps Job at Randstad (Tokyo)

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

Location

Japan , Tokyo

Salary:

9000000.00 - 15000000.00 JPY / Year

Randstad

Expiration Date

March 24, 2026

Requirements

Must have 5+ years of experience in MLOps, DevOps, or related fields
Must have proven experience with tools like Hugging Face, MLFlow, and containerization technologies (Docker, Kubernetes)
Must have strong experience with cloud platforms (AWS, Azure, GCP) and infrastructure as code (Terraform)
Must have hands-on experience in reducing inference latency and optimizing AI infrastructure
Must have proficiency in Python, with experience in ML libraries such as TensorFlow, PyTorch, and related frameworks
Must have expertise in CI/CD pipelines, version control (Git), and orchestration tools
Must have familiarity with Generative AI, prompt engineering, and deploying models at scale
Must have excellent problem-solving skills with the ability to tackle complex challenges independently

What we offer

Health insurance
Employee pension insurance
Unemployment insurance

Fulltime

Data Engineer Senior

We are looking for a highly skilled professional to lead the industrialisation o...

Location

Portugal , Lisbon

Salary:

Not provided

Inetum

Expiration Date

Until further notice

Requirements

Minimum of 5 years’ experience in MLOps, data engineering, or DevOps with a focus on ML/DL/LLM/AI agents in production environments
Strong proficiency in Python
Hands-on experience with CI/CD tools such as GitLab, Docker, Kubernetes, Jenkins
Solid understanding of ML, DL, and LLM models
Experience with ML lifecycle tools such as MLflow or DVC
Good understanding of model lifecycle, data traceability, and governance frameworks
Experience with on-premise and hybrid infrastructures
Excellent communication skills and ability to collaborate with remote teams
Proactive mindset, technical rigour, and engineering mentality
Willingness to learn, document, and standardise best practices

Job Responsibility

Analyse, monitor, and optimise ML models, tracking their performance
Design and implement CI/CD pipelines for ML models and data flows
Containerise and deploy models via APIs, batch processes, and streaming
Manage model versioning and traceability
Ensure continuous improvement and adaptation of AI use cases and ML models
Set up monitoring and alerting for model performance
Establish incident response protocols in collaboration with IT
Maintain dashboards and automated reports on model health
Implement validation frameworks for data and models (e.g., Great Expectations, unit tests, stress tests), in collaboration with Group Governance
Contribute to documentation and apply technical best practices

What we offer

Work in a constantly evolving environment
Contribute to digital impact
Opportunity for growth and development

Fulltime

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

Senior Operations Engineer

We are currently seeking an Senior Operations Engineer to join our Data Manageme...

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)
Solid hands-on experience in SQL and Python
Experience managing enterprise-scale Data/ML workflows
Strong analytical and problem-solving abilities
Fluent in English, written and oral

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

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

Senior Software Engineer – ML Model Compliance & Automation

We are seeking a highly skilled and motivated Senior Software Engineer to lead t...

Location

India , Jaipur

Salary:

Not provided

InfoObjects

Expiration Date

Until further notice

Requirements

Experience Required: 3 - 7 yrs
GoLang (preferred)
Python (preferred)
Bash
MLOps Tools: KitOps, MLModelCI, MLflow, ONNX, TensorFlow, PyTorch, Docker
SBOM & Security: Syft, Grype, Trivy, CycloneDX, SPDX
CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD
Infra: Kubernetes, Docker, Helm, Terraform
Cloud: AWS, GCP, Azure (EKS/GKE/ECS preferred)
Version Control: Git, GitOps

Job Responsibility

Model Packaging & Artifact Management: Design and implement workflows for packaging ML models using KitOps, ONNX, MLflow, or TensorFlow SavedModel
Manage model artifact versioning, registries, and reproducibility
Ensure artifact integrity, consistency, and traceability across CI/CD pipelines
Model Profiling & Optimization: Automate model profiling (latency, size, ops) using MLModelCI, TorchServe, or ONNX Runtime
Apply quantization, pruning, and format conversions (e.g., FP32→INT8) for optimization
Embed profiling and optimization checks into CI/CD pipelines to assess deployment readiness
Compliance & SBOM Generation: Develop pipelines to generate and validate SBOMs for ML models
Implement compliance checks for licensing, vulnerabilities, and security using CycloneDX, SPDX, Syft, or Trivy
Validate schema, dependencies, and runtime environments for production readiness
Cloud Integration & Deployment: Automate model registration, endpoint creation, and monitoring setup in AWS/GCP/Azure

Fulltime

Senior Machine Learning Engineer (Infrastructure)

We are looking for an experienced MLOps Engineer to join our team as a Senior Ma...

Location

United States , Boston

Salary:

152800.00 - 224100.00 USD / Year

SimpliSafe

Expiration Date

Until further notice

Requirements

5+ years of experience in software engineering, data engineering, or a related field, with at least 3 years focused on MLOps or ML infrastructure
Deep hands-on experience with AWS or similar public clouds, including compute, networking, container orchestration, and observability stacks
Hands-on experience with: CI/CD pipelines, Docker
Kubernetes
Infrastructure-as-code tools (e.g., Terraform, Cloud Formation)
Proficiency in programming languages like Python, and familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch)
Solid understanding of ML lifecycle management, including experiment tracking, versioning, and monitoring
LLM application development, including prompt engineering and evaluation
Strong communication skills for partnering with cross-functional technical and non-technical teams

Job Responsibility

Lead the architecture, deployment, and optimization of scalable ML model serving systems for real-time and batch use cases
Collaborate with data scientists, engineers, and stakeholders to operationalize ML models
Develop CI/CD pipelines for ML models enabling rapid, safe, and consistent model releases
Design, implement, and own comprehensive production monitoring for ML models/systems
Manage cloud infrastructure, primarily in AWS or other major public clouds, to support ML workloads
Drive best practices in model versioning, observability, reproducibility, and deployment reliability
Serve in an on-call rotation as a first responder for software owned by your team

What we offer

A mission- and values-driven culture and a safe, inclusive environment where you can build, grow and thrive
A comprehensive total rewards package that supports your wellness and provides security for SimpliSafers and their families
Free SimpliSafe system and professional monitoring for your home
Employee Resource Groups (ERGs) that bring people together, give opportunities to network, mentor and develop, and advocate for change
Participation in our annual bonus program, equity, and other forms of compensation
A full range of medical, retirement, and lifestyle benefits

Fulltime

Senior MLOps

Randstad

Location:
Japan , Tokyo

Category:
IT - Software Development

Contract Type:
Employment contract

Salary:

Job Description:

Requirements:

Additional Information:

Job Posted:
February 10, 2026

Expiration:
April 09, 2026

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Randstad

Location:Japan , Tokyo

Category:IT - Software Development

Contract Type:Employment contract

Salary:

Job Description:

Requirements:

Additional Information:

Job Posted:February 10, 2026

Expiration:April 09, 2026

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Contract Type:
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Job Posted:
February 10, 2026

Expiration:
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