AI/ML Engineer

The AI/ML Engineer will be responsible for developing end-to-end machine learning solutions, building scalable AI pipelines, deploying models into production, integrating Generative AI technologies, and optimizing model performance. This role requires strong programming skills, cloud experience, MLOps knowledge, and expertise with modern AI frameworks. Responsibilities

• Design, develop, train, evaluate, and deploy machine learning and deep learning models for enterprise applications.
• Develop Generative AI solutions using Large Language Models (LLMs) such as OpenAI GPT, Llama, Claude, Gemini, or similar foundation models.
• Build Retrieval Augmented Generation (RAG) applications using vector databases and embedding models.
• Fine-tune pre-trained language models using domain-specific datasets.
• Develop AI-powered chatbots, virtual assistants, recommendation engines, and predictive analytics solutions.
• Build scalable data pipelines for feature engineering, data preprocessing, model training, and inference.
• Deploy machine learning models using Docker, Kubernetes, REST APIs, and cloud-native services.
• Implement MLOps best practices including CI/CD pipelines, model versioning, automated retraining, monitoring, and governance.
• Integrate AI models with enterprise applications, databases, and third-party APIs.
• Optimize model performance, latency, scalability, and inference costs.
• Perform feature engineering, hyperparameter tuning, and model evaluation using industry-standard metrics.
• Develop ETL pipelines and process structured and unstructured datasets.
• Collaborate with data scientists, software engineers, DevOps engineers, and business stakeholders to deliver AI solutions.
• Implement responsible AI practices, security controls, model explainability, and compliance standards.
• Create technical documentation, architecture diagrams, and deployment guides.
• Stay current with emerging AI technologies, research papers, and industry best practices.

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or related field.
• 8 years of experience developing Machine Learning and AI solutions.
• Strong programming experience using Python.
• Experience with TensorFlow, PyTorch, Scikit-learn, and Hugging Face Transformers.
• Experience developing applications using Large Language Models (LLMs).
• Experience with Prompt Engineering and Retrieval Augmented Generation (RAG).
• Experience with Vector Databases such as Pinecone, ChromaDB, Weaviate, or FAISS.
• Strong knowledge of NLP, Deep Learning, Computer Vision, and Machine Learning algorithms.
• Experience deploying models using Docker and Kubernetes.
• Experience building REST APIs using FastAPI or Flask.
• Experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
• Experience with MLflow, Kubeflow, Airflow, or similar MLOps platforms.
• Experience with SQL and NoSQL databases.
• Familiarity with Git, CI/CD pipelines, and Agile methodologies.
• Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications

• Experience with OpenAI API, Azure OpenAI, AWS Bedrock, or Google Vertex AI.
• Experience with LangChain, LlamaIndex, LangGraph, CrewAI, or Semantic Kernel.
• Knowledge of Spark, Databricks, or distributed computing.
• Experience with Snowflake, Databricks, Delta Lake, or Data Lakes.
• AI/ML certifications from AWS, Azure, Google Cloud, or Databricks.
• Experience building enterprise-scale AI applications.

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