2 Mlrun Jobs

You will collaborate with other data scientists, data/ML engineers, designers, project managers, and business subject matter experts on interdisciplinary projects in various industry sectors to support business objectives using data & analytics. Your role requires a high level of collaboration, willingness to listen and learn from colleagues, and the ability to challenge thoughtfully while focusing on impact. You should continuously seek ways to enhance processes and work closely with your team members to drive iterative change and improvement. While emphasizing the importance of using the appropriate tools for each task, you will also consider clients" current environments and preferences. Commonly used tools include Python, PySpark, TensorFlow, PyTorch, Databricks, SQL, Docker, and Kubernetes. Additionally, proprietary tools like Kedro, CuasalNex, and MLRun are utilized. Collaboration with cloud service providers such as AWS, GCP, and Azure is a regular practice. As a Data Scientist, your responsibilities will include: - Solving complex business challenges for clients globally through advanced Machine Learning and statistical methods - Leading the research and development of cutting-edge AI and deep learning solutions - Identifying high-potential machine learning R&D initiatives applicable to various industries - Collaborating with QuantumBlack leadership and clients to align business problems with analytics and AI solutions - Working with a diverse team to develop end-to-end analytics solutions that drive tangible impact for clients - Contributing to one of the most skilled and diverse data science teams in the industry Your impact at McKinsey will involve working on impactful projects across diverse industries, collaborating with QB/Labs teams, and developing innovative ML systems to address business challenges efficiently. You will have the opportunity to grow as a technologist and leader by working on real-world problems and engaging with industry experts to deliver value to clients effectively. Your qualifications and skills should include: - A bachelor's or master's degree in computer science, machine learning, applied statistics, mathematics, engineering, or artificial intelligence - 2+ years of technical experience in machine learning, advanced analytics, and statistics - Proficiency in Python programming - Demonstrated application of advanced analytical and statistical methods in practical scenarios - Strong presentation and communication skills to convey complex concepts to technical and non-technical audiences - Knowledge of engineering standards and QA/risk management - Experience in GenAI application development and API integration using tools like Langchains, Crew.AI, and AutoGen is advantageous - Readiness to travel domestically and internationally for project requirements,

Position Title: AI/ML Engineer Company: Cyfuture India Pvt. Ltd. Industry: IT Services and IT Consulting Location: Sector 81, NSEZ, Noida (5 Days Work From Office) Website: www.cyfuture.com About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e.g., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise 1. Cloud Computing & Deployment Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. 2. Machine Learning & Deep Learning Strong command of frameworks: TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. 3. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI , Flask , or Django . Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). 4. Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing: Apache Spark, Dask, Ray . 5. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning . A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. 6. Resource Optimization Efficient use of compute resources: GPUs, TPUs, CPUs . Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. 7. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports . Udisha Parashar Senior Talent Acquisition Specialist Mob: +91- 9301895707 Email: udisha.parashar@cyfuture.com URL: www.cyfuture.com