Senior AI/ML Engineer

Senior AI/ML Engineer

Posted Today by Infosat IT Services LLC

Negotiable
Undetermined
Remote
Remote

Summary: We are looking for a Senior AI/ML Engineer to design, develop, and optimize advanced AI and machine learning solutions. The ideal candidate will have extensive experience in building production-grade AI/ML systems and deploying models in cloud environments. This role involves collaboration with cross-functional teams to deliver innovative AI-driven products. Strong expertise in machine learning, deep learning, and MLOps is essential.

Key Responsibilities:

  • Design, develop, train, evaluate, and deploy machine learning and deep learning models for business-critical applications.
  • Build and optimize end-to-end AI/ML pipelines for data ingestion, feature engineering, model training, validation, and deployment.
  • Develop and implement Generative AI and Large Language Model (LLM) solutions using modern AI frameworks.
  • Fine-tune foundation models and optimize model performance for production environments.
  • Build Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
  • Develop scalable APIs and microservices for AI model inference and integration.
  • Work closely with Data Engineers, Data Scientists, Product Managers, and Business Stakeholders to identify AI opportunities and deliver solutions.
  • Implement MLOps best practices including CI/CD, model monitoring, governance, and automated retraining pipelines.
  • Ensure model reliability, scalability, security, explainability, and compliance requirements.
  • Evaluate emerging AI technologies and recommend innovative approaches to improve products and business processes.
  • Mentor junior engineers and contribute to AI architecture decisions and technical leadership initiatives.

Key Skills:

  • 8+ years of Software Engineering and Machine Learning experience.
  • 5+ years of hands-on Machine Learning and AI development experience.
  • Strong proficiency in Python.
  • Expertise with Machine Learning frameworks:
    • TensorFlow
    • PyTorch
    • Scikit-Learn
    • XGBoost
  • Experience with Large Language Models (LLMs) and Generative AI.
  • Experience with:
    • OpenAI
    • Anthropic Claude
    • Google Gemini
    • Open-source LLMs (Llama, Mistral, etc.)
  • Strong experience with Prompt Engineering and Fine-Tuning techniques.
  • Experience building RAG (Retrieval-Augmented Generation) solutions.
  • Hands-on experience with:
    • LangChain
    • LangGraph
    • LlamaIndex
    • Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Milvus)
  • Experience developing REST APIs and microservices.
  • Strong SQL and NoSQL database experience.
  • Experience with distributed data processing frameworks.
  • Strong understanding of machine learning algorithms, statistics, and model evaluation techniques.

Salary (Rate): undetermined

City: undetermined

Country: USA

Working Arrangements: remote

IR35 Status: undetermined

Seniority Level: undetermined

Industry: IT

Detailed Description From Employer:

Senior AI/ML Engineer

Client: Confidential
Location: Remote (USA)
Duration: Long Term Contract
Employment Type: Contract / C2C / W2
Interview Mode: Video Interview


Job Title:

Senior AI/ML Engineer


Job Summary:

We are seeking a highly skilled Senior AI/ML Engineer to design, develop, deploy, and optimize advanced Artificial Intelligence and Machine Learning solutions. The ideal candidate will have extensive experience building production-grade AI/ML systems, developing scalable data pipelines, implementing Large Language Model (LLM) solutions, and deploying machine learning models in cloud environments.

This role requires strong expertise in machine learning, deep learning, generative AI, MLOps, data engineering, and cloud technologies. The candidate will collaborate with cross-functional teams to deliver innovative AI-driven products and business solutions.


Key Responsibilities:

  • Design, develop, train, evaluate, and deploy machine learning and deep learning models for business-critical applications.
  • Build and optimize end-to-end AI/ML pipelines for data ingestion, feature engineering, model training, validation, and deployment.
  • Develop and implement Generative AI and Large Language Model (LLM) solutions using modern AI frameworks.
  • Fine-tune foundation models and optimize model performance for production environments.
  • Build Retrieval-Augmented Generation (RAG) solutions using vector databases and enterprise knowledge sources.
  • Develop scalable APIs and microservices for AI model inference and integration.
  • Work closely with Data Engineers, Data Scientists, Product Managers, and Business Stakeholders to identify AI opportunities and deliver solutions.
  • Implement MLOps best practices including CI/CD, model monitoring, governance, and automated retraining pipelines.
  • Ensure model reliability, scalability, security, explainability, and compliance requirements.
  • Evaluate emerging AI technologies and recommend innovative approaches to improve products and business processes.
  • Mentor junior engineers and contribute to AI architecture decisions and technical leadership initiatives.

Required Skills:

  • 8+ years of Software Engineering and Machine Learning experience.
  • 5+ years of hands-on Machine Learning and AI development experience.
  • Strong proficiency in Python.
  • Expertise with Machine Learning frameworks:
    • TensorFlow
    • PyTorch
    • Scikit-Learn
    • XGBoost
  • Experience with Large Language Models (LLMs) and Generative AI.
  • Experience with:
    • OpenAI
    • Anthropic Claude
    • Google Gemini
    • Open-source LLMs (Llama, Mistral, etc.)
  • Strong experience with Prompt Engineering and Fine-Tuning techniques.
  • Experience building RAG (Retrieval-Augmented Generation) solutions.
  • Hands-on experience with:
    • LangChain
    • LangGraph
    • LlamaIndex
    • Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Milvus)
  • Experience developing REST APIs and microservices.
  • Strong SQL and NoSQL database experience.
  • Experience with distributed data processing frameworks.
  • Strong understanding of machine learning algorithms, statistics, and model evaluation techniques.

Cloud & DevOps Requirements:

  • Strong experience with AWS, Azure, or Google Cloud Platform.
  • Experience with:
    • Docker
    • Kubernetes
    • CI/CD Pipelines
    • GitHub Actions
    • Jenkins
    • Terraform
  • Experience implementing MLOps solutions using:
    • MLflow
    • SageMaker
    • Vertex AI
    • Azure ML
    • Kubeflow

Preferred Qualifications:

  • Experience building enterprise AI platforms and AI-powered products.
  • Experience working with multimodal AI models.
  • Knowledge of Responsible AI, AI Governance, and Model Risk Management.
  • Experience with Data Engineering tools such as Spark, Databricks, Kafka, and Airflow.
  • Experience in Healthcare, Finance, Insurance, Retail, Aviation, or Enterprise SaaS environments.
  • Exposure to Agentic AI and Multi-Agent Systems.
  • Experience leading AI initiatives and mentoring engineering teams.

Education:

  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Machine Learning, or related field.