AI/ML Engineer Openings: 10 Experience:5+yrs Location: Remote Key Skills Required: • Generative AI: Strong understanding of LLMs, LangGraph, LangChain, and RAG pipelines • ML & NLP: Solid grasp of machine learning and NLP fundamentals • Backend Development: Proficient in FastAPI and microservices architecture • Project Ownership: Ability to explain project architecture, internals, and components • Python: Strong coding and problem-solving capabilities Show more Show less

Job Title: GenAI Architect Experience: 8–10 Years Location: Remote Job Type: Contract Job Summary: We are looking for a highly experienced GenAI Architect to lead the design and implementation of Generative AI solutions. The ideal candidate will have a strong background in AI/ML, hands-on experience with LLMs, and the ability to architect scalable and secure AI platforms. Key Responsibilities: Design end-to-end architectures for Generative AI systems Lead model fine-tuning, prompt engineering, and deployment strategies Collaborate with data scientists, engineers, and business teams to define AI solutions Implement and optimize LLM pipelines using tools like LangChain, Transformers, and vector databases Ensure security, scalability, and performance of AI solutions Stay up to date with the latest in GenAI, LLMs, and AI infrastructure Must-Have Skills: Strong experience with LLMs (e.g., GPT, LLaMA, Claude) Python, Transformers, LangChain Experience with vector databases (e.g., FAISS, Pinecone, ChromaDB) Cloud platforms (Azure, AWS, or GCP) Knowledge of CI/CD, MLOps, and containerization (Docker/Kubernetes) Nice to Have: Experience in building AI chatbots and autonomous agents Exposure to frameworks like LangGraph or AutoGPT Prior experience in enterprise AI product development Show more Show less

Job Title: MLOps Architect Experience: 10+ Years Location: Remote Type-Contractual About the Role: We are seeking experienced MLOps Engineers to join our growing team of AI/ML professionals. The ideal candidate will have deep experience in machine learning deployment pipelines , infrastructure automation , and monitoring , with a passion for building scalable and reliable systems. This is a remote full-time opportunity with a competitive compensation package. Key Responsibilities: Design, develop, and maintain robust CI/CD pipelines for deploying machine learning models into production. Package and deploy models built with TensorFlow or PyTorch using Azure ML , AWS SageMaker , or GCP Vertex AI . Automate containerization using Docker , and manage deployment using Kubernetes (preferred). Collaborate with data scientists and engineers to streamline model training, evaluation, and deployment workflows. Implement monitoring and alerting systems using tools such as Prometheus , Grafana , and Azure Monitor . Ensure system reliability, availability, and performance optimization across environments. Maintain and manage version control using Git and CI/CD pipelines using GitLab CI/CD or equivalent. Work in a Linux environment, writing scripts to automate deployment, logging, and maintenance tasks. Required Skills: Strong hands-on experience with Docker , CI/CD pipelines , and Linux-based deployments . Experience with cloud platforms: Azure ML (preferred), AWS , or GCP . Proficiency in Python scripting and automation. Familiarity with ML model deployment pipelines and infrastructure as code. Experience with monitoring tools like Grafana , Prometheus , and Cloud-native logging/alerting systems . Working knowledge of Kubernetes (preferred). Ideal Candidate Profile: 6+ years of experience in MLOps, DevOps , or related backend infrastructure roles. Proven experience in deploying TensorFlow/PyTorch models in production environments using Azure ML and GitLab CI/CD . Demonstrated expertise in monitoring , alerting , and performance tuning of ML systems. Strong problem-solving, communication, and documentation skills. Show more Show less