5 Ml Systems Jobs

Job Type: Contract Job Summary We are seeking a highly skilled and mathematically grounded Machine Learning Engineer to join our AI team. The ideal candidate will have 5+ years of ML experience with a deep understanding of machine learning algorithms, statistical modeling, and optimization techniques, along with hands-on experience in building scalable ML systems using modern frameworks and tools. Key Responsibilities Design, develop, and deploy machine learning models for real-world applications. Collaborate with data scientists, software engineers, and product teams to integrate ML solutions into production systems. Understand the mathematics behind machine learning algorithms to effectively implement and optimize them. Conduct mathematical analysis of algorithms to ensure robustness, efficiency, and scalability. Optimize model performance through hyperparameter tuning, feature engineering, and algorithmic improvements. Stay updated with the latest research in machine learning and apply relevant findings to ongoing projects. Required Qualifications Mathematics & Theoretical Foundations Strong foundation in Linear Algebra (e.g., matrix operations, eigenvalues, SVD). Proficiency in Probability and Statistics (e.g., Bayesian inference, hypothesis testing, distributions). Solid understanding of Calculus (e.g., gradients, partial derivatives, optimization). Knowledge of Numerical Methods and Convex Optimization. Familiarity with Information Theory, Graph Theory, or Statistical Learning Theory is a plus. Programming & Software Skills Proficient in Python (preferred), with experience in libraries such as: o NumPy, Pandas, Scikit-learn, Matplotlib, Seaborn Experience with deep learning frameworks: o TensorFlow, PyTorch, Keras, or JAX Familiarity with ML Ops tools: o MLflow, Kubeflow, Airflow, Docker, Kubernetes Experience with cloud platforms (AWS, GCP, Azure) for model deployment. Machine Learning Expertise Hands-on experience with supervised, unsupervised, and reinforcement learning. Understanding of model evaluation metrics and validation techniques. Experience with large-scale data processing (e.g., Spark, Dask) is a plus. Preferred Qualifications Masters or Ph.D. in Computer Science, Mathematics, Statistics, or a related field. Publications or contributions to open-source ML projects. Experience with LLMs, transformers, or generative models. Location- Remote (Chennai - possible to travel Chennai for meetings)

Dream11 is seeking a talented Senior Machine Learning Scientist to drive the development and deployment of our ML solutions. If you have experience in building, deploying, and maintaining ML systems at scale, along with a strong foundation in Python, SQL, and ML frameworks, you'll be crucial in executing experiments, managing project lifecycles, and mentoring the team. Your Role Execute clean experiments rigorously against pertinent performance guardrails and analyze performance metrics to infer actionable findings. Develop and maintain services with proactive monitoring , incorporating best industry practices for optimal service quality and risk mitigation. Break down complex projects into actionable tasks that adhere to set management practices and ensure stakeholder visibility. Manage the end-to-end lifecycle of large-scale ML projects from data preparation, model training, deployment, monitoring, and upgrading experiments. Leverage a strong foundation in ML, statistics, and deep learning to adeptly implement research-backed techniques for model development. Stay abreast of the best ML practices and industry developments to mentor and guide team members. Qualifiers 3-5 years of experience in building, deploying, and maintaining ML solutions . Extensive experience with Python, SQL, TensorFlow/PyTorch , and at least one distributed data framework (Spark/Ray/Dask). Working knowledge of Machine Learning, probability statistics, and Deep Learning Fundamentals . Experience in designing end-to-end machine learning systems that work at scale.

Dream11 is seeking a highly skilled Lead Machine Learning Scientist to drive the development and implementation of scalable ML solutions. If you have 5-10 years of experience in building and maintaining ML systems, are proficient in predictive modeling, and have a proven track record of leading data science teams, you'll be instrumental in shaping our product's intelligence and impact. Your Role Implement appropriate success metrics , drive rapid experimentation of new POCs, and present the impacts to stakeholders. Drive knowledge sharing sessions within and across teams while maintaining continuous feedback channels with teammates to ensure building growth paths. Own respective services by following best practices in service maintainability , understanding and acting on the risks and opportunities involved. Prioritize roadmaps while balancing impact, effort, resources, and team requirements to complete initiatives within committed timelines. Develop and evaluate predictive and prescriptive models using appropriate mathematical methods like supervised and unsupervised learning, frequentist statistics, and estimation methods. Design large-scale ML systems with advanced ML frameworks like TensorFlow/Keras/PyTorch for training and inferencing at scale. Ensure cross-team alignment towards business/project goals by driving visibility of initiatives, managing conflicts, and highlighting implementation blocks. Qualifiers 5 - 10 years of experience in building and maintaining ML solutions at scale . Proficient in predictive modeling (ML, DL/RL) and experimentation/causal inference methods . At least 1 year of experience in managing a team of data scientists and handling cross-functional stakeholders. Proven track record of designing end-to-end ML systems which can handle the scale.

Responsibilities: Work experience of 3+ years with Deep Learning and Neural networks. Researching new models and machine learning algorithms Designing prototypes and conducting experiments to guide engineering efforts Creating ML applications based on client/customer requirements Tell business stories through model outcomes and data. Analyzing test results to improve models Exploring and visualizing data to identify potential issues that might affect model performance Preparing data sets from various sources (APIs, databases, text files, etc.) for algorithm use Production deployment and maintenance of ML Systems Skills required for this position include: Advanced math and stats skills (calculus, linear algebra, Bayesian statistics) A degree in a related field (math, computer science, statistics) Strong teamwork, problem-solving, and analytical abilities Knowledge of data science Proficiency in coding and programming languages (Python, SQL) Practical experience with ML frameworks and libraries Knowledge of software architecture, data modeling, and data structures Knowledge of running ML algorithms on cloud platforms (AWS, AZURE, Google cloud)

We are looking for a highly skilled Python Backend Developer with a minimum of 4+ years of experience. The candidate will develop and scale platforms to run real-time computer vision models, productionize machine learning models with API designs, and deploy models using Django or any UI. This role requires expertise in Python, Kubernetes, Docker, cloud platforms (Azure, GCP, or AWS), CI/CD, and RESTful APIs. The ideal candidate should have experience building and maintaining ML systems, working with GPU/CPU usage, and performing load, unit, and regression testing. Proficiency in FastAPI, strong communication skills, and the ability to adapt to fast-changing environments are essential.