15 Ml Systems Jobs

Sanas is revolutionizing the way we communicate with the world's first real-time algorithm, designed to modulate accents, eliminate background noises, and magnify speech clarity. Pioneered by seasoned startup founders with a proven track record of creating and steering multiple unicorn companies, our groundbreaking GDP-shifting technology sets a gold standard. Sanas is a 200-strong team, established in 2020. In this short span, we've successfully secured over $100 million in funding. Our innovation have been supported by the industry's leading investors, including Insight Partners, Google Ventures, Quadrille Capital, General Catalyst, Quiet Capital, and other influential investors. Our reput...

Role Overview: You will be part of the Oracle Cloud Infrastructure (OCI) team, reimagining operations for the enterprise cloud by building cutting-edge AI systems. As an ML Engineer, you will drive the transformation of cloud operations by developing intelligent AI solutions that proactively manage cloud environments, boost operational excellence, and enhance the customer experience. Key Responsibilities: - Lead the development of AI agents tailored for cloud operations, ensuring scalability, reliability, and alignment with customer needs. - Architect and implement tools and frameworks to accelerate AI agent development, experimentation, deployment, and monitoring. - Design robust methodolog...

Function/ Department: Data & Analytics. Job Purpose : 'As an MLOps Engineer, you will be responsible for deploying, scaling, and monitoring ML & GenAI models in production. You will own the infrastructure, automation, and observability layer while collaborating with ML Engineers and Data Scientists to ensure models (LLMs, embeddings, recommendation systems, etc.) are reliably served at scale. This role combines DevOps best practices with ML-specific needs, ensuring smooth model lifecycle management and robust GenAI-powered applications. Key / Primary Responsibilities: ' '* Design and manage CI/CD pipelines for ML model deployment. * Provision and maintain scalable infrastructure using Kubern...

Role Overview: At Oracle Cloud Infrastructure (OCI), we are on a mission to revolutionize cloud infrastructure operations by leveraging cutting-edge AI systems. As an ML Engineer, you will play a crucial role in driving the transformation of cloud operations at OCI. Your primary responsibility will be to develop intelligent AI solutions that proactively manage cloud environments, enhance operational excellence, and elevate the overall customer experience. This is a unique opportunity for you to tackle deep technical challenges and contribute to shaping the future of autonomous cloud technology. Key Responsibilities: - Lead AI Agent Development: Take charge of designing and developing AI agen...

Greeting From BMW Techworks!! Experience: 5 to 12 Years Location: Bangalore Notice period: immediate to 60days Join our team to industrialize and deploy sophisticated machine learning models on the edge, powering the next generation of our innovative products. We're looking for a Senior ML Engineer to drive the end-to-end lifecycle of our ML systems, from initial model development to robust, real-world deployment on resource-constrained devices. This role involves designing, developing, and deploying highly efficient and optimized ML models, including Large Language Models (LLMs) and Small Language Models (SLMs), directly onto edge devices. You will be instrumental in building the core infra...

Requirements 45 years of experience as an ML Engineer or Applied Scientist in production Strong Python skills (FastAPI/Flask), with PyTorch or TensorFlow Proficient in building data pipelines and deploying ML systems Experience with LLMs, embeddings, RAG systems, and vector DBs (PGVector/Postgres preferred) Hands-on with multiple LLM providers (OpenAI, Anthropic, Google, open-source) Knowledge of containerization and deployment (Docker, Kubernetes, AWS/GCP, CI/CD) Bonus: Familiarity with LangGraph/LangChain, vLLM, Ray, LLM eval tools, or event-driven systems Responsibilities Build and scale ML pipelines for Novas AI teammates Implement agentic AI workflows with LLMs and orchestration framewo...

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 (calcu...

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...

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 b...

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 instru...

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 effective...

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 ...

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 ...

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 (calcu...

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.