Job SummaryWe are looking for a skilled AI/ML Engineer with 5-7 years of experience in building and deploying scalable machine learning and Generative AI solutions. The ideal candidate should have a strong foundation in core AI/ML concepts, deep learning, NLP, and experience with Generative AI frameworks.Who We Are Looking ForAn enthusiastic self-starter who will work with minimal guidance, has strong Python programming skills, and hands-on experience deploying end-to-end AI/ML solutions. A first-principle understanding of databases, deep learning and LLMs is also required.Required Skills and Qualifications1.3+ years of work experience in Python programming for AI/ML, deep learning, and Generative AI model development2.Proficiency in TensorFlow/PyTorch, Hugging Face Transformers and Langchain libraries3.Hands-on experience with NLP, LLM prompt design and fine-tuning, embeddings, vector databases and agentic frameworks4.Strong understanding of ML algorithms, probability and optimization techniques5.6+ years of experience in deploying models with Docker, Kubernetes, and cloud services (AWS Bedrock, SageMaker, GCP Vertex AI) through APIs, and using MLOps and CI/CD pipelines6.Familiarity with retrieval-augmented generation (RAG), cache-augmented generation (CAG), retrieval-integrated generation (RIG), low-rank adaptation (LoRA) fine-tuning7.Ability to write scalable, production-ready ML code and optimized model inference8.Experience with developing ML pipelines for text classification, summarization and chat agents9.Prior experience with SQL and noSQL databases, and Snowflake/DatabricksWhat You Will Be DoingAs an AI/ML Engineer in the AI center of excellence (COE) at DataZymes, you will be developing and maintaining end-to-end AI solutions to business problems. Key responsibilities are listed below:1.Design, develop, and deploy AI/ML models for various applications, including NLP and structured data2.Implement, prompt, fine-tune, and optimize Generative AI models, such as LLMs and diffusion models3.Develop and maintain data pipelines, feature engineering workflows, and model training infrastructure4.Work with large-scale datasets, ensuring data quality and pre-processing for training and inference5.Optimize model performance, reducing latency, and improving efficiency for real-time AI applications6.Deploy models using MLOps best practices on cloud platforms (AWS, GCP)7.Collaborate with cross-functional teams, including data engineers, software developers, and product managers to develop AI solutions to business problems8.Implement responsible AI practices, ensuring fairness, interpretability, and ethical AI adoption
Job Title
AI/ML Engineer