Roles & Responsibilities: Design, develop, and maintain scalable, high-performance web applications. Work across the full stack front-end (React/Angular/Vue) and back-end (Node.js, Python, Java, or .NET). Implement RESTful APIs and integrate third-party services. Manage databases (SQL/NoSQL) and ensure data integrity and security. Optimize application performance and troubleshoot complex issues. Lead architecture design, participate in code reviews, and enforce coding best practices. Collaborate with UI/UX designers, product managers, and QA teams to deliver end-to-end solutions. Mentor junior developers and provide technical guidance to the team. Deploy, monitor, and maintain applications on cloud platforms (AWS, Azure, GCP). Stay updated with emerging technologies to drive continuous improvement. Requirements: Bachelors/Master’s in Computer Science, Engineering, or equivalent. 7+ years of experience in full-stack development. Strong knowledge of front-end frameworks (React, Angular, or Vue). Expertise in server-side technologies (Node.js, Python, Java, or .NET). Hands-on experience with databases (MySQL, PostgreSQL, MongoDB, etc.). Familiarity with CI/CD, containerization (Docker, Kubernetes), and microservices. Excellent problem-solving, leadership, and communication skills. Role & responsibilities
Roles & Responsibilities: Collect, preprocess, and analyze large structured and unstructured datasets. Develop, train, and optimize machine learning and deep learning models. Build predictive models for classification, regression, recommendation, and NLP/vision tasks. Design and implement scalable ML pipelines and deploy them into production environments. Conduct feature engineering, model selection, hyperparameter tuning, and validation. Monitor model performance, detect drift, and improve accuracy over time. Collaborate with product, engineering, and business teams to translate business problems into data-driven solutions. Document methodologies, maintain reproducibility, and ensure ethical AI practices. Work with big data tools (Spark, Hadoop) and cloud ML services (AWS Sagemaker, GCP AI, Azure ML). Stay updated with advancements in AI/ML and contribute to innovation initiatives. Requirements: Bachelors/Master’s/PhD in Computer Science, Data Science, Statistics, or related field. 5+ years of proven experience in Data Science & Machine Learning. Strong coding skills in Python (pandas, numpy, scikit-learn, TensorFlow, PyTorch). Solid understanding of statistical modeling, probability, and linear algebra. Hands-on with data visualization tools (Tableau, Power BI, matplotlib, seaborn). Experience in deploying ML models in production (Docker, Kubernetes, APIs). Knowledge of MLOps best practices and cloud AI platforms. Strong analytical mindset, critical thinking, and communication skills.
About the Role We are looking for an experienced AI Engineer to design, develop, and deploy AI/ML-based solutions that power our products and internal systems. You will collaborate with data scientists, software engineers, and product teams to build scalable and production-ready AI applications. Key Responsibilities Design, develop, and deploy machine learning and deep learning models for production environments. Work with large-scale datasets performing data preprocessing, feature engineering, and exploratory data analysis (EDA). Collaborate with cross-functional teams to integrate AI models into production-grade systems and services (e.g., via APIs, microservices). Optimize model performance and scalability through experimentation, tuning, and monitoring. Implement MLOps practices CI/CD for ML, model versioning, automated retraining pipelines, and model monitoring. Research and evaluate emerging AI technologies, frameworks, and tools for potential adoption. Contribute to the development of internal AI tools, libraries, and best practices. Required Skills & Qualifications Education: B.Tech/M.Tech/MS/Ph.D. in Computer Science, AI, Data Science, or related field. Experience: 48 years in AI/ML engineering, with hands-on deployment of models into production environments. Strong programming skills in Python (and familiarity with libraries such as TensorFlow, PyTorch, scikit-learn, etc.). Experience with data processing frameworks (Pandas, NumPy, Spark, etc.). Proficiency in ML lifecycle management tools and cloud platforms (AWS Sagemaker, Azure ML, GCP Vertex AI, MLflow, Kubeflow, etc.). Solid understanding of software engineering principles version control (Git), CI/CD, containerization (Docker), and orchestration (Kubernetes). Good understanding of mathematics, statistics, and algorithms for AI/ML. Excellent problem-solving and communication skills. Preferred / Nice-to-Have Skills Experience with LLMs (e.g., fine-tuning or deploying GPT, Llama, or other transformer-based models). Knowledge of Computer Vision (OpenCV, Detectron2) or NLP frameworks (Hugging Face, spaCy). Exposure to Vector Databases , Retrieval-Augmented Generation (RAG) , or Generative AI applications. Familiarity with data pipelines (Airflow, Prefect) and monitoring tools (Prometheus, Grafana). Contributions to open-source ML/AI projects. Role & responsibilities
FIND ON MAP