Job Title

We are looking for a highly skilled AI/ML Engineer who can design, build, and deploy intelligent systems that power next‑generation enterprise solutions. This role is ideal for someone who thrives in a fast‑moving environment, enjoys solving complex problems, and wants to contribute to scalable, global‑impact products.Key Responsibilities Machine Learning & AI Development: • Build, train, and optimize ML models for classification, prediction, NLP, and generative AI use cases. • Develop scalable pipelines for data ingestion, preprocessing, feature engineering, and model deployment. • Implement LLM‑based solutions, including fine‑tuning, prompt engineering, and retrieval‑augmented generation (RAG).Engineering & Architecture: • Design and maintain production‑grade ML systems using cloud platforms (AWS, Azure, GCP). • Build APIs, microservices, and automation workflows to integrate ML models into enterprise applications. • Ensure models meet performance, reliability, and security standards.Data & Analytics: • Work with structured and unstructured datasets at scale. • Develop monitoring systems for model drift, data quality, and performance metrics. • Collaborate with data engineers and product teams to translate business needs into technical solutions.Research & Innovation: • Stay current with advancements in AI/ML, including LLMs, transformers, vector databases, and MLOps best practices. • Prototype new ideas and evaluate emerging tools, frameworks, and architectures.Required Skills & Experience: • 3–7 years of experience in AI/ML engineering or applied data science. • Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit‑learn). • Experience with LLMs, embeddings, vector stores (FAISS, Pinecone, Chroma), and RAG pipelines. • Hands‑on experience with cloud services (AWS Sagemaker, Azure ML, GCP Vertex AI). • Solid understanding of algorithms, data structures, and distributed systems. • Experience deploying ML models into production environments. • Familiarity with CI/CD, Docker, Kubernetes, and MLOps workflows.Preferred Qualifications: • Experience with generative AI (LLMs, diffusion models, multimodal systems). • Knowledge of big‑data tools (Spark, Databricks, Kafka). • Exposure to enterprise software domains such as ERP, supply chain, or financial systems. • Contributions to open‑source AI/ML projects.Soft Skills: • Strong problem‑solving and analytical thinking. • Excellent communication and documentation skills. • Ability to work independently in a remote, distributed team. • Ownership mindset with a passion for innovation.