AI/ML Engineer

Location: Remote / Hybrid / Onsite (Specify Location)
Duration: Long-Term Contract / Full-Time
Experience: 5+ Years
Visa Status: U.S. Citizens, s(on W2), GC-EAD (on W2), -EAD, and Other Authorized-to-Work Candidates Welcome. No Sponsorship Available Now or in the Future.

Job Summary

We are seeking a talented AI/ML Engineer to design, develop, deploy, and optimize Machine Learning and Generative AI solutions. The ideal candidate will have hands-on experience building scalable AI models, developing data pipelines, and deploying production-grade ML applications on cloud platforms.

You will collaborate with data scientists, software engineers, product managers, and business stakeholders to deliver innovative AI-powered solutions that drive business value.

Key Responsibilities

• Design, build, train, and deploy machine learning and deep learning models.
• Develop and optimize Generative AI, LLM, and NLP solutions.
• Build scalable data pipelines and feature engineering workflows.
• Fine-tune foundation models for domain-specific use cases.
• Implement model monitoring, evaluation, and performance optimization.
• Integrate AI/ML solutions into enterprise applications and APIs.
• Deploy ML models using MLOps best practices.
• Collaborate with cross-functional teams to identify AI opportunities.
• Ensure security, scalability, and reliability of AI applications.
• Stay current with emerging AI technologies, frameworks, and industry trends.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI, Machine Learning, or related field.
• 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
• Strong programming skills in Python.
• Experience with ML frameworks such as:
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • Keras
• Experience with NLP and Large Language Models (LLMs).
• Strong understanding of Machine Learning algorithms and model evaluation techniques.
• Experience with SQL and NoSQL databases.
• Experience with REST APIs and microservices architecture.
• Familiarity with Git, CI/CD, and Agile methodologies.

Preferred Qualifications

• Experience with Generative AI platforms such as OpenAI, Anthropic, Gemini, or Azure OpenAI.
• Hands-on experience with LangChain, LlamaIndex, CrewAI, AutoGen, or Semantic Kernel.
• Experience building RAG (Retrieval-Augmented Generation) applications.
• Experience with vector databases:
  • Pinecone
  • ChromaDB
  • Weaviate
  • FAISS
• Cloud experience with AWS, Azure, or Google Cloud Platform.
• Knowledge of Docker, Kubernetes, and MLOps tools.
• Experience with Databricks, Snowflake, or Spark.