Senior Data Scientist
Role details
Job location
Tech stack
Job description
English. Responsibilities : 1. Model Development & Deployment: Deploy and train models on AWS SageMaker (using TensorFlow / PyTorch). 2. Model Tuning & Optimization: Fine-tune and optimize models using techniques like quantization and distillation, and tools like Replicate. 3. Generative AI Solutions: Design and implement advanced GenAI solutions, including prompt engineering and retrieval-augmented generation (RAG) strategies. 4. LLM Workflows: Develop agentic LLM workflows that incorporate tool usage, memory, and reasoning for complex problem-solving. 5. Scalability & Performance: Maximize model performance on AWS by leveraging techniques such as model compilation, distillation, and quantization, using AWS-specific features. 6. Collaboration: Work closely with Data Engineering, DevOps, and MLOps teams to integrate models into production pipelines and workflows. Benefits : * Professional training and certifications covered by the company (AWS, FinOps, Kubernetes, etc.) *
Requirements
International work environment * Referral program: enjoy cooperation with your colleagues and get a bonus * Company events and social gatherings (happy hours, team events, knowledge sharing, etc.) * Wellbeing and professional coaching * English classes * Soft skills training Country-specific benefits will be discussed during the hiring process. Automat-it is committed to fostering a workplace that promotes equal opportunities for all and believes that a diverse workforce is crucial to our success. Our recruitment decisions are based on your experience and skills, recognizing the value you bring to our team. LI-hybrid #LI-AIT Requirements : 1. 4 years of experience in machine learning or data science roles with deep learning (NLP, LLMs) expertise. 2. Expert in Python and deep learning frameworks (PyTorch / TensorFlow) and hands-on with AWS ML services (especially SageMaker and Bedrock). 3. Proven experience with generative AI and fine-tuning large language models. 4. Strong experience deploying ML solutions on AWS cloud infrastructure and familiarity with MLOps best practices. 5. Excellent communication skills and ability to work directly with customers in a consulting capacity. 6. A master's degree in a relevant field and AWS ML certifications are a plus. Remote Work : Employment Type : Full-time Key Skills Laboratory Experience, Mammalian Cell Culture, Biochemistry, Assays, Protein Purification, Research Experience, Next Generation Sequencing, Research & Development, cGMP, Cell Culture, Molecular Biology, Flow Cytometry Experience : years Vacancy : 1 #J-18808-Ljbffr