Artificial Intelligence Engineer

Job Title: AI Engineer(Complete Remote) Employment Type: Contract (C2C)/Fulltime Experience in Years: 8+ Job Overview: Highly skilled AI Engineer with a strong background in Python, GCP, Kubernetes, Docker, Kafka, worked on building microservices, scalable solutions, API development. Experience using AI Services and solutions and bringing these into production. Mongo or similar NoSQL DB experience. Knowledge on prompt engineering, observability frameworks, PromQL, Grafana are good to have. Key Responsibilities: • LLM Development and Fine-tuning : • Private and Secure Model Deployment: • Generative AI Solutions: • Cloud Infrastructure and MLOps: • Vector Databases & Embeddings: • Model Monitoring & Optimization: • Consuming AI Services and Solutions: • API Development & Microservices: Building and deploying scalable solutions using APIs and Microservices Building Kafka streams Required Skills & Experience: Education: • Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field. A Ph.D. is a plus. Experience: • 5+ years of experience in developing and deploying AI models. • Extensive hands-on experience with GCP tools, especially Vertex AI, BigQuery, and Cloud Functions. • Proven track record of fine-tuning LLMs (e.g., GPT, T5, BERT) for specific use cases, with a deep understanding of transfer learning techniques. • Strong expertise in MLOps, including automation of model training, deployment, versioning, and monitoring using Kubernetes, Docker, CI/CD, and TensorFlow Extended (TFX). • Solid understanding of vector databases and embedding-based search techniques using FAISS, Pinecone, or similar technologies. • Experience with private cloud deployments and ensuring data security, compliance, and privacy within the AI development lifecycle. • Experience building APIs and Microservices. Technical Skills: • Machine Learning Frameworks: Expertise in TensorFlow, PyTorch, JAX, and transformer-based architectures (e.g., Gemini, GPT, T5, BERT). • Cloud Technologies: Advanced knowledge of Google Cloud Platform (GCP), including Vertex AI, BigQuery, and Cloud Functions. • MLOps: Expertise in CI/CD pipelines, model versioning, model monitoring, and model deployment using Kubernetes, Docker, and TensorFlow Extended (TFX). • Embedding Models: Experience with embedding generation, semantic search, and vector databases like FAISS and Pinecone. • Programming Languages: Python (expert), SQL, No SQL (MongoDB),Shell scripting. • Data Engineering: Experience with large-scale data processing using BigQuery, Kafka. • APIs, Microservices, Kafka streams • Prompt Engineering • Good to have skills - Prometheus, PromQL, Grafana Soft Skills: • Strong problem-solving ability with the capacity to translate complex business problems into AI-driven solutions. • Excellent communication skills for explaining complex technical concepts to cross-functional teams and stakeholders. • Ability to thrive in a fast-paced, collaborative environment.