AI/ML Engineer

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.