Senior Software Engineer - AI/ML

Devsinc is hiring aSenior AI/ML Engineer with4+ years of experience, including development of LLM or generative AI applications. The ideal candidate brings strongmachine learning fundamentals and expertise inPython backend services and APIs, RAG, semantic search, AI agents, and scalable ML infrastructure, using commercial and open-source models.

You will own theend-to-end AI lifecycle, from experimentation and evaluation to deployment, optimization, and monitoring, ensuring reliable, scalable, secure, and cost-efficient solutions. The role also involves architectural decisions, mentoring engineers, and collaborating with clients and cross-functional teams to deliver measurable business impact.

Responsibilities

• Design, develop, and deployAI/ML and LLM-based applications, includingAI agents, tool-using systems, and human-in-the-loop workflows, to solve business problems.
• Build scalabletraining, fine-tuning, evaluation, and inference pipelines, with experiment tracking and model versioning.
• Develop and optimizeRAG and semantic-search systems using embeddings, document chunking, vector search, reranking, and grounding.
• Buildbackend APIs, microservices, and real-time inference services usingPython, FastAPI, Flask, or Django.
• Improve model quality, latency, throughput, and cost through experimentation,hyperparameter tuning, quantization, batching, and caching.
• ImplementMLOps, automated testing, CI/CD, and production monitoring, supported by evaluation datasets, quality criteria, regression tests, and human review.
• Guide architectural decisions and cloud deployment, ensuringscalability, reliability, security, and resource efficiency, with safeguards against prompt injection, data leakage, unauthorized access, and unsafe outputs.
• Evaluate emerging AI technologies and measure feature effectiveness throughproduct analytics or A/B testing.
• Mentor engineers, collaborate with technical and non-technical stakeholders, and document designs, experiments, and outcomes.

• Bachelor’s degree inComputer Science,Software Engineering,Data Science, or a related field.
• 4+ years of post-graduation professional experience in AI/ML engineering, with demonstrated ownership of production AI systems and hands-on experience developingLLM or generative AI applications.
• Strong production-levelPython skills, with hands-on experience inPyTorch and/or TensorFlow and solid knowledge of machine learning, neural networks, NLP, feature engineering, and model optimization.
• Experience integrating commercial or open-sourceLLMs, including prompt design, structured outputs, tool calling, context management, and model limitations.
• Hands-on experience buildingRAG or semantic-search systems, including embeddings, chunking, retrieval, reranking, and grounding, using vector-search solutions such aspgvector, Pinecone, Weaviate, Qdrant, Milvus, or Elasticsearch.
• Experience developing and deployingAPIs, microservices, or inference services usingFastAPI, Flask, Django, or equivalent frameworks, with proficiency inSQL and PostgreSQL or MySQL.
• Experience deploying AI solutions onAWS, Azure, or Google Cloud, with working knowledge ofGit, Docker, automated testing, CI/CD, and MLOps, including experiment tracking, model versioning, and monitoring.
• Understanding ofAI evaluation, regression testing, human review, and security and privacy risks.
• Ability to own technical decisions, guide engineers, and communicate effectively with clients and cross-functional stakeholders.

Preferred Skills & Experience

• Experience with AI frameworks such asLangChain, LlamaIndex, or LangGraph, and evaluation tools such asLangSmith, Langfuse, or Ragas, is a plus.
• Experience withHugging Face Transformers, vLLM, Ollama, LoRA/PEFT fine-tuning, or self-hosted models is preferred.
• Familiarity withMLflow, Kubeflow, Kubernetes, Terraform, distributed systems, or GPU acceleration is a plus.
• Experience withdata orchestration, asynchronous processing, caching, or messaging, using tools such asAirflow, Redis, Celery, Kafka, or RabbitMQ, is preferred.
• Knowledge ofadvanced retrieval, knowledge graphs, recommendation systems, computer vision, multimodal AI, or A/B testing and product analytics is a plus.