General
We are looking for AI/ML Engineers to join our client team and contribute to design, development, and deployment of advanced machine learning systems that drive intelligent automation and data-driven decision-making across various industries.
Responsibilities/Activities
- Collect, preprocess, and clean data sets for model training and evaluation
- Design, train, and optimize machine learning and deep learning models for production use
- Build scalable data and model pipelines and integrate models into production systems
- Collaborate with software engineers and data teams to integrate AI components into business applications and APIs
- Conduct model evaluation, tuning, and validation to ensure reliability, accuracy, and performance
- Research and prototype emerging AI techniques (LLMs, multimodal learning, generative AI) to enhance solution capabilities
- Monitor and maintain model performance and accuracy in production environments
Requirements
Technical
- At least 4 years of previous experience in a similar role
- Strong programming skills in Python and major ML frameworks (PyTorch, TensorFlow, Scikit-learn)
- Proven experience with deep learning, natural language processing (NLP), with strong knowledge of third-party large language models (LLMs)
- Working experience with cloud platforms (AWS, Azure, or GCP) and MLOps tools (MLflow, Kubeflow, Docker, Kubernetes)
- Experience with data engineering workflows: ETL pipelines, feature stores, or distributed data systems
- Knowledge of AI orchestration tools (LangChain, LlamaIndex, or similar) and model deployment at scale
- Familiar with RAG-based approaches that support AI models with retrieved context to improve accuracy and relevance
- Solid understanding of software engineering principles (version control, testing, CI/CD)
- Good understanding of Agile/Scrum methodologies
Education
- University degree in Computer Science, Data Science, or another related field
Others
- Good level of English (oral and written)
- Strong analytical and problem-solving skills
- Ability to learn quickly and adapt to new technologies
- Comfortable working under tight deadlines
Nice to have requirements
- Experience with multi-agent systems or autonomous AI workflows (e.g., LangGraph, AutoGen)
- Contributions to open-source AI projects or published research
- Exposure to multimodal AI systems (text, image, or audio)