Roles & Responsibilities

Demonstrated hands-on experience with generative AI technologies, including LLM architectures and frameworks.
Strong programming skills in Python or R and experience with ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.).
Proven experience training, evaluating, and deploying ML models in real-world scenarios.
Solid understanding of data preprocessing, feature engineering, and model lifecycle.

Requirements:

Build AI Agents with the domain context for specialised tasks.
Integrate the agents with the applications.
Build, train, and deploy gen AI.
Implement agents in production environments (APIs, microservices, cloud architecture).

Job description

Why do we need you?

At Appsilon, we empower global organizations to make smarter decisions with data. Our solutions help Fortune 500 companies discover new drugs, save lives, optimize operations, and unlock millions in value. To do this, we rely on robust, scalable, beautifully engineered data systems.

We’re looking for an AI Engineer who combines strong engineering fundamentals with hands-on ML expertise - someone who can turn complex data into smart, production-ready solutions that matter.

What you’ll do:

Build AI Agents with the domain context for specialised tasks.
Integrate the agents with the applications.
Build, train, and deploy gen AI.
Perform feature engineering, model validation, and experiments.
Implement agents in production environments (APIs, microservices, cloud architecture).
Document your work, follow best MLOps practices, and help shape AI development standards at Appsilon.
Work closely with Data Engineers, Developers, and Analysts to integrate Gen AIML solutions into full-scale applications.

We’re looking for someone with:

Demonstrated hands-on experience with generative AI technologies, including LLM architectures and frameworks.
Strong programming skills in Python or R and experience with ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost, etc.).
Proven experience training, evaluating, and deploying ML models in real-world scenarios.
Solid understanding of data preprocessing, feature engineering, and model lifecycle.
Ability to integrate ML solutions with applications (APIs, cloud endpoints, microservices).
Excellent communication skills and a collaborative approach to teamwork.

Nice to have:

Experience with cloud deployment (AWS, Azure, GCP) and containerization (Docker / Kubernetes).
Knowledge of MLOps tools (MLflow, Vertex AI, SageMaker, DVC, Airflow).
Experience working with large-scale or scientific datasets (biostatistics, genomics, pharma).
Understanding of data engineering / ETL concepts.
Awareness of AI ethics, bias, and responsible AI principles.

What we offer:

100% remote work, flexible schedule, and a global team culture.
Competitive B2B compensation with transparent ranges.
Work on impactful, real-world products used by enterprise clients and scientific industries.
Budget and dedicated time for professional development (courses, certs, conferences).
A chance to collaborate with a brilliant group of researchers and industry experts.
Modern equipment and tools for efficient development.
Supportive environment with room for innovation, experimentation, and ownership.

Recruitment Process

General interview with the People Team.
Technical task (Codility test).
Technical interview
Final interview with the Head of Technology
Offer.

Appsilon is committed to being a diverse and inclusive workplace. We encourage applicants of different backgrounds, cultures, genders, experiences, abilities, and perspectives to apply. All qualified applicants will receive consideration for employment without regard to race, color, national origin, religion, sexual orientation, gender, gender identity, age, physical disability, or length of time spent unemployed.

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