9 Ml Systems Jobs

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)

You will be part of the AI squad within the CDO office of the bank, playing a critical role in driving AI adoption and enablement across the bank's functions. Your main responsibility will be to deploy as a member of the functional AI Squads. Your key responsibilities include: Strategy: - Delivering, building, and maintaining solutions for AI use cases and enhancing functionalities of AI tools within the bank. Business: - Accelerate the delivery of AI use cases for various Business & Functions of the bank. - Responsible for implementing product roadmaps, product improvement, building applications with modern architecture design, RESTful web services / APIs, web-based application enhancements for processing large data volumes and real-time streaming, and product deployment with appropriate SDF controls. - Supporting applications in production, analyzing and resolving issues, performing RCA analysis, and implementing solutions. - Acting as a technical subject matter expert and go-to person for all technical requirements within your team. Risk Management: - Adhering to all SDF controls and Data Governance Standards of the bank. Governance: - Developing and implementing change management plans for successful adoption of AI solutions across the organization. - Providing training and support to business users to help them understand and leverage AI tools and technologies. - Fostering a culture of innovation and continuous improvement by promoting the benefits of AI and encouraging experimentation. Regulatory & Business Conduct: - Displaying exemplary conduct and living by the Groups Values and Code of Conduct. - Taking personal responsibility for embedding the highest standards of ethics, regulatory and business conduct across Standard Chartered Bank. - Collaboratively identifying, escalating, mitigating, and resolving risk, conduct, and compliance matters. Key stakeholders include CDO Squads, Business Partners, ITO, internal staff, clients, and 3rd parties. Other responsibilities include embedding Here for good and Groups brand and values, performing other assigned responsibilities under Group, Country, Business, or Functional policies and procedures, identifying and prioritizing AI use cases with significant business value, and developing business cases for AI projects. You are expected to have skills and experience in building and deploying machine learning models, implementing Generative AI solutions, mentoring and guiding a team of machine learning engineers and data scientists, optimizing feature engineering and model tuning, and driving the adoption of advanced ML algorithms. Qualifications: - Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) for building and deploying production-grade machine learning models. - Training in usage and development of LLMs and proficiency in Prompt Engineering. - Language proficiency in English. Standard Chartered is an international bank that values difference, advocates inclusion, and aims to drive commerce and prosperity through unique diversity. They offer core bank funding for retirement savings, medical and life insurance, time-off benefits, flexible working options, proactive wellbeing support, a continuous learning culture, and the opportunity to be part of an inclusive and values-driven organization. If you are looking for a purpose-driven career and want to work for a bank that makes a difference, Standard Chartered welcomes your unique talents and is excited to see what you can bring to the team.,

About this role: Wells Fargo is seeking a Principal Engineer. In this role, you will: Act as an advisor to leadership to develop or influence applications, network, information security, database, operating systems, or web technologies for highly complex business and technical needs across multiple groups Lead the strategy and resolution of highly complex and unique challenges requiring in-depth evaluation across multiple areas or the enterprise, delivering solutions that are long-term, large-scale and require vision, creativity, innovation, advanced analytical and inductive thinking Translate advanced technology experience, an in-depth knowledge of the organizations tactical and strategic business objectives, the enterprise technological environment, the organization structure, and strategic technological opportunities and requirements into technical engineering solutions Provide vision, direction and expertise to leadership on implementing innovative and significant business solutions Maintain knowledge of industry best practices and new technologies and recommends innovations that enhance operations or provide a competitive advantage to the organization Strategically engage with all levels of professionals and managers across the enterprise and serve as an expert advisor to leadership Required Qualifications: 7+ years of Engineering experience, or equivalent demonstrated through one or a combination of the following: work experience, training, military experience, education Desired Qualifications: Strong programming skills (preferably Python) Knowledge of data science, statistics & mathematics Experience with cloud implementation (preferable GCP) Ability to analyze and extract relevant features for training machine learning models Design & build machine learning systems that use AI to learn & improve Job Expectations: Designing ML systems Model evaluation AI Model Use cases implementation in production Gen AI use case implementation Data Science Natural language processing Problem Solving

As an Engineering Lead at Bolo AI, a company dedicated to utilizing AI to optimize Energy processes, you will play a crucial role in expanding the engineering team and overseeing the delivery of cutting-edge products focused on Generative AI systems. Your responsibilities will encompass managing a talented group of applied scientists, MLOps engineers, and backend developers who are dedicated to developing high-performance platforms for LLM training, RAG, LLM agent orchestration, and enterprise deployments. Your primary objective will be to ensure that the team collaborates effectively to deliver top-tier products within set timelines and with exceptional quality standards. You will be instrumental in driving product excellence, facilitating the swift introduction of new features, functionalities, and AI-driven solutions for our valued customers. Moreover, you will be tasked with defining the technical roadmap, establishing operational frameworks, and upholding engineering standards. Reporting to the CTO and closely working with the CEO, you will engage with research and product teams to shape the company's trajectory and achieve tangible outcomes through state-of-the-art AI technologies. Key Responsibilities: - Architecting scalable and high-performance systems to support LLM pipelines, RAG infrastructure, and agentic workflows - Building, nurturing, and expanding a top-tier engineering team spanning platform engineering, ML infra, and backend systems - Overseeing the end-to-end delivery process of mission-critical AI products from conceptualization to deployment - Collaborating effectively with founders, research scientists, and product managers to align on technical strategies and business objectives - Establishing best practices in software development, MLOps, DevSecOps, and system design to ensure code quality and architectural integrity - Spearheading initiatives to enhance system performance, optimize LLM inference efficiency, and drive cost efficiencies across cloud environments - Engaging with enterprise clients and partners to comprehend requirements, solicit feedback, and facilitate solution delivery Qualifications: - Over 10 years of engineering experience with a minimum of 5 years in building and leading engineering teams, ideally in dynamic startup environments - Profound expertise in constructing production ML systems, encompassing model training, optimization, and large-scale deployment (LLM, RAG, agents, classification, etc.) - Strong background in backend and systems engineering with proficiency in Python and microservice architecture - Prior exposure to hybrid deployments (on-prem, VPC) and cloud-native infrastructure (AWS, GCP, Azure) - Demonstrated ability to scale engineering organizations, implement processes, and drive cross-functional collaborations - Passion for addressing real-world challenges using innovative ML and AI solutions - Educational background in Computer Science or related field (M.Tech/MS/PhD), with preference for candidates from esteemed institutions like IIT/NIT/BITS Desirable Skills: - Familiarity with CPU- and GPU-optimized ML inference frameworks such as BOLT, TorchScript, Triton, ONNX, or vLLM - Proficiency in LLM training methodologies (e.g., LoRA, QLoRA, RLHF, MoE), LLM Agents, multilingual NLP, or recommendation systems - Track record of publications in renowned ML/NLP conferences or patents in the AI/ML domain - Previous involvement in startup environments, particularly within the enterprise or SaaS sectors Join us at Bolo AI for: - Competitive Compensation: A competitive base salary - Ownership & Impact: Equity options to participate in our growth and success - Hybrid Work Environment: Flexibility to collaborate in-person and work remotely to ensure work-life balance - Growth & Opportunity: Engage in a pivotal stage where your contributions will shape our journey and unlock new opportunities - Culture of Respect & Collaboration: Join a team that values humility, respect, and teamwork, celebrating collective achievements.,

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.