Machine Learning Engineer

Are you a builder who wants to solve hard problems in AI for Science?
Atinary Technologies is revolutionizing R&D and Materials Discovery. Our platform, SDLabs, empowers researchers to accelerate scientific breakthroughs using AI-driven experimentation. We are looking for a Machine Learning Engineer to join the AI & Data Engineering (AIDEn) team and help us build the next generation of our ML product.

In this role, you will engineer the systems that translate Bayesian Optimization research and Generative AI concepts into scalable, production-grade software. You will serve as the bridge between our Research Scientists and our core platform, helping us scale from “algorithm” to “industry-changing product.”

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

As a key member of the AIDEn team, you will take ownership of the engineering behind our ML capabilities. You will work on our model-serving infrastructure, our core Adaptive Experimentation library, and our evolving data processing architecture. This is a role for a versatile engineer with a systems mindset who is proficient in Python, cares about code quality, and is fascinated by the intersection of probabilistic machine learning and backend software engineering.

Responsibilities

* Collaborate with the Research team to refactor, optimize, and productionize experimental code (e.g., transitioning research prototypes into robust production features).

* Design and maintain the architecture for serving diverse ML models ensuring low latency and high availability.

* Build the backend systems required to ingest, validate, and store complex experimental data. You will help architect pipelines using tools like (MLFlow, AWS Sagemaker, AWS Batch, Ray) to support large-scale compute and inference workflows.

* Automate the lifecycle of our models. Ensure that when our researchers prototype a new optimization strategy, it can be deployed seamlessly using CI/CD, containerization, and orchestration.

* Contribute to the integration of Generative AI into our platform (using LangSmith / LangChain), focusing on RAG, fine-tuning, and reliable structured outputs for scientific workflows.

* Work with Site Reliability Engineering (SRE) to ensure our ML services are cost-optimized, monitored, and resilient.

Requirements
Must-have:

* 3+ years of experience in Machine Learning Engineering or Backend Engineering with a heavy data focus.

* Python Expertise: You write clean, type-hinted, testable code. You are familiar with modern standards.

* Data Proficiency & Tooling: Demonstrated proficiency in data handling, including experience with relevant tools such as Pandas, NumPy, scikit-learn, etc.

* ML Framework fluency: Comfortable with PyTorch, Tensorflow, Keras or equivalent.

* Infrastructure Mindset: Experience with containerization (Docker)

Nice-to-have:

* A genuine interest in how AI can accelerate scientific discovery.

* Bayesian Optimization: Experience with, or a strong desire to learn, BoTorch and GPyTorch.

* LLM Stack: Familiarity with the modern GenAI stack (LangChain, LangSmith, Vector Databases).

* Product-Centric Mindset: You think beyond the model. You care about inference latency, API design, and how ML features integrate into the full-stack application to deliver a seamless user experience.

* Cloud Environment Experience: Experience with cloud services and environments (AWS preferred).

* Data Engineering Experience: Experience handling data pipelines and distributed compute frameworks (e.g., Ray, Dask, or Spark).

Benefits
WHY YOU WOULD LOVE WORKING WITH US:

* Industry Impact: Your code will directly enable the discovery of new materials, drugs, and sustainable technologies.

* Independence &Versatility: We value engineers who can see the big picture. You won’t be siloed into a narrow task; instead, you will have the agency to design end-to-end solutions—whether that means optimizing a mathematical kernel or architecting a distributed computing system.

* Technical Challenge: You will solve unique challenges related to “small data,” uncertainty quantification, and the integration of LLMs into scientific rigor.

* Growth: You will work alongside researchers and engineers, constantly learning about state-of-the-art algorithms and system design.

* Join a Winning Culture: We’re committed to a flexible, innovative, and supportive work environment. We have a hybrid policy of 2 home office days per week.

* Celebrate the Moments that Matter: We believe in celebrating our team’s success and important milestones. From company-wide achievements to personal wins, we make sure to recognize and appreciate the moments that contribute to our shared journey.

Please note that only candidates who are legally authorized to work in Switzerland will be considered for this position.

Please submit your resume and a cover letter. In your cover letter, please mention a technical challenge you faced when moving a machine learning model from a “notebook experiment” to a “production system,” or explain why you are interested in the AI4Science space.

Note that candidates need to be prepared to submit two references from past employers and/ or 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.