Are you a passionate MLOps Engineer looking to make an impact in a dynamic and fast-paced environment? Then join Atinary Technologies (Lausanne, Switzerland) and its talented team to shape a future where AI is at the core of the R&D landscape! SDLabs, our main product, is an end-to-end software suite that uses machine learning to optimize processes and accelerate materials discovery.

As a smaller team, we are all generalists and are constantly looking for people that can take a problem and solve it. We use Python to build SDLabs which helps teams around the world to improve their experimentation workflows. We don't expect you to have a background in everything we use, but we do expect strong software engineering foundations and a background with either one of our key languages.

About Atinary Technologies

Atinary Technologies is a fast-growing AI startup revolutionizing R&D through cutting-edge machine learning. We empower researchers and enterprises to accelerate discovery with our AI-driven platform. Our team values innovation, collaboration, and agility.

Role Overview

We are looking for an MLOps Engineer to work closely with our AI research team and AI & data engineering team. You will build and maintain end-to-end ML pipelines, enabling researchers to deploy models efficiently while ensuring reproducibility, scalability, and observability in production environments, as well as empowering SDLabs users to train their own models using our infrastructure.

Responsibilities

• Design, implement, and maintain ML pipelines for training, validation, deployment, serving, and monitoring.


• Collaborate with AI researchers to operationalize models and experiments.


• Work with data engineering to integrate feature stores, data pipelines, and datasets into ML workflows.


• Implement reproducibility and versioning for datasets, models, and experiments (MLflow, W&B, or similar).


• Manage model serving infrastructure (Docker, Kubernetes, AWS stack, serverless solutions).


• Monitor deployed models for drift, accuracy, and performance.


• Automate ML workflows and CI/CD pipelines for ML systems.


• Partner with SecOps for secure and compliant deployment of models and data pipelines.


• Stay ahead of the curve by engaging with the latest developments in MLOps and Data Engineering. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices.

Requirements

Must-have:

• 3+ years of experience in MLOps, ML engineering, or related roles.


• Hands-on experience with ML lifecycle tools (MLflow, Kubeflow, SageMaker, Vertex AI).


• Strong Python skills and familiarity with ML frameworks (PyTorch, TensorFlow, scikit-learn).


• Experience with containerized deployment and orchestration (Docker, Kubernetes).


• Knowledge of data pipelines, ETL, and distributed systems.


• Ability to collaborate with research and engineering teams in a fast-paced startup environment.


• Hands-on experience monitoring of production systems including (Kibana, Prometheus, LangSmith, AWS Cloudwatch, etc)


• Hands-on experience doing cost optimization of production systems.

Nice-to-have:

• Experience with feature stores, real-time inference pipelines, or distributed training.


• Familiarity with Airflow, Prefect, or similar orchestration tools.


• Startup experience in AI/ML environments.


• Prior experience and familiarity KServe, AWS Batch, AWS SageMaker and AWS Bedrock.


• LLMOps experience including cost optimization, finetuning, RAG, sandboxing.

Benefits
Why Join Us

• Directly enable AI research and production at a pioneering ML startup.


• Work with a collaborative team of researchers, engineers, and data scientists.


• Influence the MLOps strategy and ML infrastructure from the ground up.


• Competitive compensation, benefits, and equity options.

Please submit your resume and a cover letter highlighting your relevant experience and verifiable track record. Candidates need to be prepared to submit two references from past employers and clients in the final steps of the interview process.

Atinary is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We seek a friendly, respectful, professional, collaborative and inspiring atmosphere and work environment for every employee, collaborator and client regardless of gender, physical appearance, sexual orientation, disability, age, race or religion.

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