About the Role

Apexon is seeking an experienced AI/ML Engineer with strong expertise in LLM development, MLOps, and building scalable GenAI solutions. You will design, build, and operationalize AI/ML systems that support enterprise clients across healthcare, BFSI, retail, and digital transformation engagements.

The ideal candidate has hands-on experience building end-to-end machine learning pipelines, optimizing large language model workflows, and deploying secure ML systems in production environments.

Responsibilities

LLM & AI Solution Development

• Build, fine-tune, evaluate, and optimize Large Language Models (LLMs) for client-specific use cases such as document intelligence, chatbot automation, code generation, and workflow orchestration.
• Develop RAG (Retrieval-Augmented Generation) pipelines using enterprise knowledge bases.
• Implement prompt engineering, guardrails, hallucination reduction strategies, and safety frameworks.
• Work with transformer-based architectures (GPT, LLaMA, Mistral, Falcon, etc.) and develop optimized model variants for low-latency and cost-efficient inference.

Machine Learning Engineering

• Develop scalable ML systems including feature pipelines, training jobs, and batch/real-time inference services.
• Build and automate training, validation, and monitoring workflows for predictive and GenAI models.
• Perform offline evaluation, A/B testing, performance benchmarking, and business KPI tracking.

MLOps & Platform Engineering

• Build and maintain end-to-end MLOps pipelines using:
• AWS SageMaker, Databricks, MLflow, Kubernetes, Docker, Terraform, Airflow
• Manage CICD pipelines for model deployment, versioning, reproducibility, and governance.
• Implement enterprise-grade model monitoring (data drift, performance, cost, safety).
• Maintain infrastructure for vector stores, embeddings pipelines, feature stores, and inference endpoints.

Data Engineering & Infrastructure

• Build data pipelines for structured and unstructured data using:
• Snowflake, S3, Kafka, Delta Lake, Spark (PySpark)
• Work on data ingestion, transformation, quality checks, cataloging, and secure storage.
• Ensure all systems adhere to Apexon and client-specific security, IAM, and compliance standards.

Cross-Functional Collaboration

• Partner with product managers, data engineers, cloud architects, and QA teams.
• Translate business requirements into scalable AI/ML solutions.
• Ensure model explainability, governance documentation, and compliance adherence.

Basic Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, AI/ML, Data Science, or related field.
• 4+ years of experience in AI/ML engineering, including 1+ years working with LLMs/GenAI.
• Strong experience with Python, Transformers, PyTorch/TensorFlow, and NLP frameworks.
• Hands-on expertise with MLOps platforms: SageMaker, MLflow, Databricks, Kubernetes, Docker.
• Strong SQL and data engineering experience (Snowflake, S3, Spark, Kafka).

Preferred Qualifications

• Experience implementing Generative AI solutions for enterprise clients.
• Expertise in distributed training, quantization, optimization, and GPU acceleration.
• Experience with:
• Vector Databases (Pinecone, Weaviate, FAISS)
• RAG frameworks (LangChain, LlamaIndex)
• Monitoring tools (Prometheus, Grafana, CloudWatch)
• Understanding of model governance, fairness evaluation, and client compliance frameworks.