1524 Mlops Jobs - Page 4

Role Overview: As a Senior Technical Architect specializing in Data Science & Agentic AI, you will play a crucial role in leading the end-to-end modeling lifecycle. Your main responsibilities will include problem framing, experiment design, production deployment, and monitoring. You will be tasked with setting up the technical architecture for ML/GenAI and agentic systems. While collaborating with DE/Platform teams, your primary focus will be on modeling excellence, MLOps, and AI solution architecture to impact business KPIs positively. Key Responsibilities: - Own the technical vision for data-science initiatives and translate ambiguous business goals into modellable problems, KPIs, and NFRs...

Fill below mandatory link. MLops-virtual interview with Capgemini--all locations, Monday 27th Oct 2025 Fill out form Position: - Machine Learning Ops Harvest Level: Software Engineer Job Description: Machine Learning Ops Engineer is the one whos responsible for managing and optimizing the deployment and operation of machine learning models in production environments. He/she works closely with data scientists, software engineers, and DevOps teams to ensure that machine learning models are integrated seamlessly into existing systems and can scale effectively. Role & Responsibilities Responsible for design and implementation of secure and scalable infrastructure in Azure cloud. Build and mainta...

5+ years of experience in Machine Learning, Azure and MLOps MLOps Implementation and Support Experience Python Programming - Expert and Experienced - 4 -5 years DevOps Working knowledge with implementation experience Hands-On MS Azure Cloud knowledge List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup Well verse in coding standards (flake8 etc) Agile trained to manage team effort and track through JIRA

5+ years of experience in Machine Learning, Azure and MLOps MLOps Implementation and Support Experience Python Programming - Expert and Experienced - 4 -5 years DevOps Working knowledge with implementation experience Hands-On MS Azure Cloud knowledge List Azure services required for deployment, Azure Data bricks and Azure DevOps Setup Well verse in coding standards (flake8 etc) Agile trained to manage team effort and track through JIRA

• Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, Scikit-learn, XGBoost, or LightGBM. • Strong understanding of data structures, algorithms, and statistics.

Job Location- Bangalore Years of experience -7+years Notice Period - immediate to 30days Job Description Key Responsibilities: Lead Full-cycle Development: Take charge of the complete lifecycle of machine learning models, overseeing conception, prototyping, deployment, and iterative optimization processes to enhance performance and scalability. Architect Solutions: Utilize strong software design principles to build efficient and maintainable ML applications and services that adhere to best industry practices. Collaborative Model Development: Partner with data scientists and stakeholders to address specific business challenges, thoroughly exploring available data for effective model training ...

Build and deploy real estate-specific AI & LLM solutions. Enhance dashboards, integrate ERP data, and develop intelligent apps for property insights, automation, and analytics. Work with Next.js, Python, and Hugging Face.

Key Responsibilities: Architect and lead the development of scalable AI/ML solutions across diverse domains.Design and implement systems leveraging Large Language Models (LLMs) and Agentic AI principles. Collaborate with QE teams to integrate AI into testing frameworks and CI/CD pipelines. Evaluate and implement AI services using Azure OpenAI, Google Cloud (GHCP), and other cloud platforms. Guide the development and deployment of machine learning models using best practices in MLOps. Mentor data scientists and engineers, and lead cross-functional AI initiatives. Ensure AI solutions are ethical, explainable, and aligned with business goals. Required Skills & Qualifications: 10+ years of exper...

Location: Hyderabad Role: Machine Learning Engineer Exp: 5-9 years Mode: work from office(5 days) Looking for a driven and innovative Machine Learning Engineer to help us scale and foresee problems that aren't apparent. We're seeking a hands-on individual with a strong passion for data and a proven ability to translate complex data challenges into robust, scalable machine learning solutions. In this role, you'll be a key player in developing, deploying, and maintaining ML models that directly impact our core business functions and enhance user experiences. If you thrive in a collaborative, fast-paced environment, excel at working with diverse data sources, and possess a solid foundation in m...

Role & responsibilities Experience: 6-8 years Location - Bengaluru We are looking for a Senior Data Scientist with 6-8 years extensive experience in designing, building, and evaluating machine learning models for diverse business use cases. The role requires strong fundamentals in mathematics, statistics, and computer science with a focus on model interpretability, evaluation metrics, and production-readiness . You will work on end-to-end data science projects — from hypothesis formulation, feature engineering, and model selection to rigorous evaluation and deployment. Key Responsibilities Core Modeling & Algorithmic Work Develop and optimize models for classification, regression, clustering...

About Position: We are hiring a highly skilled Machine Learning Engineer to lead the development and deployment of scalable ML solutions for enterprise applications. This role requires deep expertise in ML model development, MLOps, and cloud-native AI platforms, along with strong collaboration and solution delivery capabilities. Role: Machine Learning Engineer Location: All Persistent location Experience: 8 to 12 Years Job Type: Full Time Employment What You'll Do: You will design and implement robust ML pipelines, collaborate across teams, and deliver AI/ML solutions that drive business impact. Design, develop, and implement ML models for predictive analytics, NLP, computer vision, and reco...

AI/ML ,NLP with leadership, handling production support in live environments. Design, develop,deploy AI/ML and NLP-based solutions tailored for enterprise use cases.MLOps pipelines using MLflow, Seldon,Docker for scalable model deployment.

As a Google AI Architect, your role will involve leading the design, development, and deployment of advanced AI/ML solutions utilizing Google Cloud Platform (GCP) and Vertex AI. You should have a strong background in enterprise architecture and cloud-native AI/ML systems, with proven experience in driving end-to-end AI transformation initiatives across various industries. Key Responsibilities: - Define and drive AI/ML architecture strategies using GCP services such as Vertex AI, BigQuery ML, TensorFlow, and Generative AI Studio. - Lead the design and implementation of AI solutions across enterprise applications, data platforms, and customer-facing products. - Architect and deploy scalable, s...

Role Overview: As an Applied AI Engineer at Key, you will be responsible for taking AI and ML models from concept to production. Your main focus will be on building scalable and reliable systems using Python, cloud services, and modern MLOps practices. You will have the opportunity to own the end-to-end delivery of AI solutions, contributing to transforming professional networking by fostering authentic relationships and meaningful connections. Key Responsibilities: - End-to-end ownership of production ML systems from prototype to live services - Implement, fine-tune, and optimize models, including LLMs for search and recommendation, for performance, latency, and cost - Design, build, and ma...

As a Full Stack MLOps Developer/Engineer, you will be responsible for designing, developing, and deploying scalable machine learning solutions and cloud-native applications, ensuring seamless integration and automation across platforms. Your role will involve collaborating with data scientists and DevOps teams to automate ML workflows and deployment processes. Additionally, you will be involved in developing and maintaining end-to-end full stack applications with a focus on ML deployment and automation. Key Responsibilities: - Develop and maintain end-to-end full stack applications with a focus on ML deployment and automation. - Design, implement, and manage scalable MLOps pipelines utilizin...

As an experienced professional in the field of AI and Machine Learning, you have worked in agile, cross-functional teams and have a track record of delivering measurable impact. Your educational background includes a Masters or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Key Responsibilities: - Architect and deploy enterprise-scale AI/ML platforms such as GenAI, LLMs, agentic architectures, and MLOps/LLMOps. - Design, implement, and scale AI infrastructure using technologies like Databricks, Azure AI, Snowflake, Spark, Airflow, and related tools. - Utilize hands-on experience for production-grade model selection, fine-tuning, evaluatio...

As an AI/ML Engineer at our company, you will play a crucial role in transforming Data Science prototypes into production-ready applications, building scalable MLOps pipelines, and maintaining deployed models. Your strong background in software engineering, cloud infrastructure, and practical experience with the full ML lifecycle will be essential for success in this role. Key Responsibilities: - Refactor and optimise Data Science prototypes for performance and efficiency. - Containerise models using Docker and deploy them onto a scalable infrastructure, such as Kubernetes. - Design and build low-latency APIs to serve model predictions in real-time. - Implement CI/CD/CT pipelines to automate...

Role Overview: You are a visionary and hands-on Principal AI Engineer at AlphaSense, playing a crucial role in shaping the future of AI within the company. As the foundational pillar of the Content portfolio strategy, your mission is to research, architect, and pioneer solutions that process and extract intelligent insights from millions of unstructured documents and multi-media files daily. This is a unique opportunity to be the primary AI/ML authority, responsible for implementing cutting-edge techniques for document classification, entity extraction, and more. Key Responsibilities: - Spearhead AI Innovation: Research, evaluate, and prototype cutting-edge solutions using Large Language Mod...

Role Overview: As a Data Engineer or ML Engineer in the Tech Services- Group Chief Technology Office team at UBS, you will play a key role in driving the delivery of an innovative ecosystem of tools and services to support the bank's global AI Strategy. Your main focus will be on developing an SDK for Data Producers to build high-quality autonomous Data Products and enabling Data Consumers to easily access data and build AI use-cases. Key Responsibilities: - Lead the country team of other Senior Engineers - Engage directly with product owners and internal users to gather requirements, develop technical solutions, and execute projects - Develop an SDK (Software Development Kit) to capture dat...

Role Overview: As a Data Intelligence & AI Solution Architect at Capgemini, you will lead the design and implementation of advanced data platforms and AI-driven solutions. You will collaborate with presales, delivery, and client teams to architect scalable systems using Databricks, MLOps frameworks, and cloud-native technologies. Key Responsibilities: - Architect and design data intelligence platforms using Databricks, Apache Spark, and Delta Lake. - Lead MLOps initiatives to streamline model development, deployment, and monitoring. - Collaborate with account teams to understand client challenges and propose AI-driven solutions. - Support presales activities including RFP responses, solution...

We are seeking a Competency Leader to lead the design, development, and deployment of advanced AI and Generative AI (GenAI) solutions that deliver significant business value to our pharma clients. The ideal candidate will have extensive hands-on experience with AI/ML frameworks, cloud platforms, and MLOps, coupled with a deep understanding of GenAI technologies. Key Responsibilities: • Design, develop, and optimize AI/ML models for practical applications, ensuring high performance, scalability, and reliability. • Innovate using advanced GenAI technologies (e.g., LLMs, RAG, OpenAI APIs) to address complex business challenges. • Implement and manage end-to-end MLOps pipelines, including CI/CD,...

What you will do: ACVs Machine Learning (ML) team is looking to grow its MLOps team. Multiple ACV operations and product teams rely on the ML teams solutions. Current deployments drive opportunities in the marketplace, in operations, and sales, to name a few. As ACV has experienced hyper growth over the past few years, the volume, variety, and velocity of these deployments has grown considerably. Thus, the training, deployment, and monitoring needs of the ML team has grown as weve gained traction. MLOps is a critical function to help ourselves continue to deliver value to our partners and our customers. Successful candidates will demonstrate excellent skill and maturity, be self-motivated as...

As an AI Lead at our company, you will be responsible for spearheading the design, development, and deployment of advanced AI/ML solutions in the domain of connected vehicle analytics. Your role will require you to be a strategic thinker with hands-on expertise in machine learning platforms and a passion for turning data into actionable intelligence that drives business outcomes. Key Responsibilities: - Define and execute the end-to-end AI/ML roadmap for connected vehicle analytics, ensuring scalability, performance, and alignment with business goals. - Design robust machine learning systems using platforms such as Google Vertex AI, TensorFlow, and AutoML, tailored to real-time vehicle data ...

As an MLOps Engineer at Fractal Analytics, you will play a crucial role in building the machine learning production system and deploying state-of-the-art AI solutions for clients. You will collaborate with Data Scientists and Data Engineers to deploy and operate advanced analytics machine learning models. Your responsibilities will include: - Enabling model tracking, model experimentation, and model automation - Developing scalable ML pipelines - Building MLOps components in the machine learning development lifecycle using Model Repository such as MLFlow or Kubeflow Model Registry - Working across all phases of model development to build MLOps components - Developing the knowledge base requi...

Role Overview: You will be responsible for designing, building, and deploying end-to-end AI/ML systems in production. Your expertise in data science, including statistical analysis, experimentation, and data storytelling, will be crucial in working with large-scale, real-world datasets for model training and analysis. You should be comfortable navigating urgency, ambiguity, and fast-changing priorities while independently solving complex ML problems from idea to implementation. Additionally, your strong leadership experience building and guiding high-performing AI teams will be essential, along with hands-on experience in deep learning, NLP, LLMs, and classical ML techniques. Key Responsibil...