Lead Software Engineer

Virtusa Corp

  • Tampa, FL
  • 11 days ago

    Highlights

    We are seeking a Data Scientist with experience to design, build, and deploy GenAI and LLM-powered solutions. The role combines applied ML, prompt engineering, and MLOps to deliver scalable, production-grade AI systems.

    Numbers & Facts

    LocationTampa, FL

    Description

    We are seeking a Data Scientist with experience to design, build, and deploy GenAI and LLM-powered solutions. The role combines applied ML, prompt engineering, and MLOps to deliver scalable, production-grade AI systems.

    Key Responsibilities

    Develop and deploy LLM-based applications (RAG, chatbots, copilots, summarization, search)

    Fine-tune, evaluate, and optimize LLMs and transformer models

    Design prompt engineering strategies and guardrails for safe, reliable outputs

    Build retrieval pipelines using vector databases (FAISS, Pinecone, etc.)

    Implement end-to-end ML pipelines (data model deployment monitoring)

    Collaborate with engineering teams to integrate models via APIs and microservices

    Monitor model performance, drift, and costs; implement feedback loops

    Ensure responsible AI practices (bias mitigation, explainability, governance)

    Required Skills & Qualifications

    3-6 years of experience in Data Science / ML Engineering / Applied AI

    Strong programming in Python

    Hands-on experience with LLMs (OpenAI, Azure OpenAI, etc.)

    Experience with transformers, embeddings, and NLP pipelines

    Familiarity with RAG architectures and vector search

    Solid foundation in ML algorithms, statistics, and evaluation metrics

    Strong SQL and data handling skills

    MLOps & Engineering Skills

    Experience with model deployment (FastAPI, Flask, Docker, Kubernetes)

    Exposure to CI/CD pipelines for ML (GitHub Actions, Azure ML, SageMaker, etc.)

    Experience in model monitoring, logging, and versioning (MLflow, Weights & Biases)

    Knowledge of data pipelines (Airflow, Spark)

    Familiarity with cloud platforms (AWS, Azure, or GCP)

    Preferred Qualifications

    Experience fine-tuning LLMs (LoRA, PEFT techniques)

    Exposure to multi-modal models (text + image/audio)

    Knowledge of AI safety, hallucination mitigation, and evaluation frameworks

    Domain experience in enterprise use cases (support, search, analytics, automation)

    Soft Skills

    Strong problem-solving and experimental mindset

    Ability to translate ambiguous business problems into AI solutions

    Excellent communication with technical & non-technical stakeholders

    Education

    Bachelor's or Master's in Computer Science, AI, Data Science, Statistics, or a related field

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