Senior MLOps Platform Engineer with GenAI experience

🚀 Who we are:

Adaptiq is a technology hub specializing in building, scaling, and supporting R&D teams for high-end, fast-growing product companies in a wide range of industries.

📍 About the Product:

We are building an AI-first platform that fuses multiple maritime data sources into a unified operational picture. 
The system builds a digital twin of global maritime activity, applies behavioral analytics and predictive AI models to surface smuggling, illegal fishing, container risk, and other compliance or security threats, and presents mission-grade intelligence to both commercial and government stakeholders. 

Operating at global scale, the platform processes millions of events and terabytes of geospatial data daily, relies on cloud infrastructure and microservices, and integrates with upstream research prototypes from data science teams.

About the Role:

As a MLOps Platform Engineer, you will play a key role in helping the company scale its AI capabilities by building and owning the infrastructure and processes that support machine learning models throughout their entire lifecycle.
 

You will work closely with Data Scientists, Data Analysts, and Platform Engineers to build and improve systems for dataset and label management, model registries, experiment tracking, and model deployment.
 

Your work will help the team deliver models to production faster and more reliably, while making a direct impact on a mission-critical AI platform.

Key Responsibilities:

• Design and implement systems for dataset and label management, including versioning and customer feedback integration.
• Establish and maintain a model repository/registry with version control, lineage tracking, and local inference support.
• Lead implementation of experiment tracking and monitoring solutions for data science and generative AI, focusing on evaluation, drift detection, and reproducibility.
• Lead the deployment, lifecycle management, and continuous improvement of ML/DL models in production.
• Own model serving and inference infrastructure, including autoscaling, A/B testing, canary deployments, and latency/cost optimization.
• Enable generative AI capabilities by developing tagging tools, prompt management services, and LLM testing frameworks.
• Drive operational excellence by improving tool deployment usability and establishing granular cost visibility across environments and projects.
• Develop reusable components such as standardized data loaders, CI/CD pipelines, and automated model retraining workflows.
• Collaborate with data scientists and platform engineers to productionize ML/DL models in public cloud environments.

📍 Required Competence and Skills:

• At least 5 years of hands-on experience in MLOps / ML Platform Engineering (or equivalent ML Engineering experience with strong MLOps ownership). Able to independently design, build, and scale production ML infrastructure.
• Experience collaborating closely with Data Scientists or ML Research teams to productionize machine learning models.
• Strong Python programming skills.
• Hands-on experience in containerization, CI/CD, and public cloud platforms (AWS, Azure, or GCP) for deploying, serving, and monitoring ML models.
• Proficiency with dataset management, model versioning, experiment tracking, monitoring, and MLOps platforms (e.g. MLflow, SageMaker, or similar tools).
• Experience with machine learning frameworks (PyTorch or TensorFlow), big-data technologies (Apache Spark), and data stores such as PostgreSQL, MongoDB, and Redis.
• Experience using AI-assisted development tools and adopting Generative AI and agentic workflows in day-to-day software development.

Nice to Have:

• Java programming experience in production environments.

Why Us:

We provide 20 days of vacation leave per calendar year (plus official national holidays of a country you are based in).

We provide full accounting and legal support in all countries we operate.

We utilize a fully remote work model with a powerful workstation and co-working space in case you need it.

We offer a highly competitive package with yearly performance and compensation reviews.