MLOps Engineer

Job Description Roles & Responsibilities As a Senior Machine Learning Ops Engineer at AI71, you ll be responsible for developing, deploying, and optimizing machine learning models and systems that power our AI solutions. You will collaborate with cross-functional teams to translate business challenges into impactful AI products. What You'll Do: Model Development: Develop, train, and deploy predictive models that enhance the capabilities of our AI solutions. AI Technologies: Work with state-of-the-art AI techniques, including Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), and apply them to real-world business contexts. Cross-Functional Collaboration: Partner with business stakeholders to understand objectives and translate them into actionable machine learning tasks. Model Optimization: Continuously monitor, evaluate, and improve models based on real-world performance and evolving business needs. Data Pipeline Maintenance: Implement and manage robust data preprocessing pipelines to ensure high-quality, reliable input data for model development. Strong communication, stakeholder management, and decision-making skills, with a passion for building diverse, inclusive engineering teams. Desired Candidate Profile What You'll Bring: Master s or Ph.D. in AI, Data Science, Computer Science, Statistics, or a related field. 5+ years of experience in AI, Machine Learning, Reinforcement Learning (RL), Data Science, or a related field. Proven experience with Large Language Models (LLMs) and parameter-efficient fine-tuning methods (LoRA, QLoRA, etc.) techniques. Strong proficiency in programming languages like Python. Preference for candidates with a competitive coding background (e.g., ACM/ICPC, NOI/IOI, Top Coder, Kaggle). Experience in building and deploying LLM-powered applications using FastAPI/ Flask and Streamlit for front-end interfaces, solid understanding of REST principles, HTTP Methods, websockets and API lifecycle management; Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and libraries like Langchain, Langgraph, LlamaIndex. Experience with SQL, NoSQL (PostgreSQL, MySQL, MongoDB, Redis) and vector databases (Pinecone, Weaviate, pgvector) for structured data storage and semantic search. Demonstrated success in applying data science and machine learning to solve real-world, business-critical problems. Excellent communication and collaboration skills with the ability to work across interdisciplinary teams. Company Industry IT - Software Services Department / Functional Area IT Software Keywords MLOps Engineer Get real-time job updates only on our App