133 Ml Deployment Jobs - Page 2

Modeling & Analysis: Building, training, and validating models Cleaning and preparing data Combining and shaping data Applying descriptive and inferential statistics Azure Services & Tools : Use of Azure Notebooks, Azure Machine Learning, Azure Databricks, and Azure Synapse Analytics Integration with Kusto Query Language and Azure Data Explorer Machine Learning & Feature Engineering : Preparing data for ML in Azure Building features from nominal, text, and numeric data in Azure Developing and deploying ML models using Azure services Integration with Open-Source Tools : Azure supports Python, R, TensorFlow, PyTorch, scikit-learn, pandas, and NumPy

About the job : Zeta Global is looking for an experienced ML Engineer with industry-proven hands-on experience of delivering machine learning models to production to solve business problems. To be a good fit to join our AI/ML team, you should ideally: Be a thought leader that can work with cross-functional partners to foster a data-driven organization. Be a strong team player, have experience contributing to a large project as part of a collaborative team effort. Have extensive knowledge and expertise with machine learning best-practices and industry standards. Be able to design and execute experiments to measure the impact of new features and machine learning models on business outcomes. Em...

e-Zest, an AccionLabs company , as we are urgently hiring a Machine Learning Engineer for our Pune location. In this role, you will be responsible for designing, developing, and deploying scalable ML models that solve real-world business challenges. Youll work closely with data scientists, engineers, and product teams to deliver production-ready ML solutions with strong performance and scalability. Key Highlights of the Role: Build and deploy ML models & pipelines in production. Collaborate with data scientists to optimize algorithms for real-world use. Work with large-scale datasets for training & evaluation. Implement MLOps practices (CI/CD, model versioning, automated deployment). Develop...

5+ Years of prior experience in Data Engineering and MLOPs. 3+ Years of strong exposure in deploying and managing data science pipelines in production environments. Strong proficiency in Python programming language. Experience with Spark/PySpark and distributed computing frameworks. Hands-on experience with CI/CD pipelines and automation tools. Exposure in deploying a use case in production leveraging Generative AI involving prompt engineering and RAG Framework Familiarity with Kafka or similar messaging systems. Strong problem-solving skills and the ability to iterate and experiment to optimize AI model behavior. Excellent problem-solving skills and attention to detail. Ability to communica...

Key Responsibilities Design, fine-tune, and manage prompts for diverse enterprise LLM use cases. Operate, monitor, and troubleshoot agentic AI applications , diagnosing whether issues stem from: Prompt structure/quality Model configuration or performance Tool usage, API failures, or memory/recall issues Build diagnostic playbooks for LLM-driven failures, including fallback strategies, retries, and re-routing to human workflows. Collaborate with AI architects, ML engineers, and DevOps teams to optimize agent orchestration across platforms such as LangGraph, CrewAI, AutoGen, etc. Support integration of agentic systems with enterprise tools (Jira, ServiceNow, Glean, Confluence) via REST APIs, w...

Skills Needed : Deploying ML models in cloud (AWS, Azure, Oracle) and on-premises. CI/CD pipelines for ML. Containerization (Docker, Kubernetes). Building and maintaining data pipelines . Model monitoring and retraining. About the role: MLOps professional with 6-8 years of experience in deploying and scaling machine learning models in production environments of banks. Should be thrive at the intersection of data science and engineering, ensuring that fraud detection models move seamlessly from prototype to production. Hands-on experience with cloud platforms (AWS, Azure, Oracle) as well as on-premise deployments, and should be comfortable working with containerization, orchestration, and CI/...

We are seeking a skilled ML Ops Engineer to join our team and streamline the deployment, monitoring, and management of machine learning models at scale. You will collaborate closely with data scientists, engineers, and DevOps to build robust, scalable ML infrastructure and CI/CD pipelines for AI/ML workflows. ML Ops engineer/ML engineer Project Description The engineer is supposed to participate in various AI projects such as Demand Sensing and Forecasting, Price and Promotion Optimization and others. Details on Tech Stack Proficiency in Python. Competent knowledge of best practices for software development. Strong understanding of Data Science concepts such as supervised and unsupervised le...

We are seeking a skilled ML Ops Engineer to join our team and streamline the deployment, monitoring, and management of machine learning models at scale. You will collaborate closely with data scientists, engineers, and DevOps to build robust, scalable ML infrastructure and CI/CD pipelines for AI/ML workflows. ML Ops engineer/ML engineer Project Description The engineer is supposed to participate in various AI projects such as Demand Sensing and Forecasting, Price and Promotion Optimization and others. Details on Tech Stack Proficiency in Python. Competent knowledge of best practices for software development. Strong understanding of Data Science concepts such as supervised and unsupervised le...

We are seeking a skilled ML Ops Engineer to join our team and streamline the deployment, monitoring, and management of machine learning models at scale. You will collaborate closely with data scientists, engineers, and DevOps to build robust, scalable ML infrastructure and CI/CD pipelines for AI/ML workflows. ML Ops engineer/ML engineer Project Description The engineer is supposed to participate in various AI projects such as Demand Sensing and Forecasting, Price and Promotion Optimization and others. Details on Tech Stack Proficiency in Python. Competent knowledge of best practices for software development. Strong understanding of Data Science concepts such as supervised and unsupervised le...

dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First. Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail one of the worlds most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, Me...

Role & responsibilities Design and manage end-to-end ML pipelines for deployment and monitoring. Automate model training, retraining, and deployment workflows . Implement CI/CD for ML models to ensure reliability and scalability. Build real-time dashboards and APIs for model outputs and business consumption. Optimize cloud resources (Azure Databricks, ADF, Azure ML) for performance and cost efficiency. End-to-end model lifecycle management from development to deployment. Collaborate with data scientists, engineers, and business teams to operationalize ML solutions. Preferred candidate profile 3+ years of experience in MLOps / Data Science and model deployment . Strong skills in Python, PySpa...

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Devel...

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions. Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT t...

MLOps Engineer (Exempt) Enterprise AI/ML Organization OVERVIEW We are looking for an experienced MLOps Engineer to support our AI and ML initiatives, including GenAI platform development, deployment automation, and infrastructure optimization. You will play a critical role in building and maintaining scalable, secure, and observable systems that power scalable RAG solutions, model training platforms, and agentic AI workflows across the enterprise. RESPONSIBILITIES Design and implement CI/CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails). Provision an...

Role & responsibilities Understand workflows/processes and devise strategies for the areas applicable to AI-based implementation. Translate eLearning requirements into AI-driven automation strategies. Define data requirements and provide datasets for AI model training specific to eLearning. Design and maintain data pipelines (Azure Data Factory, Databricks, Synapse Analytics) to ensure clean, structured content for training. Apply governance frameworks (Azure Policy, Purview, DLP) to ensure responsible AI practices. Ensure fairness and transparency in AI models using Fair learn and Interpret ML. Develop and optimize AI models for automating eLearning processes, including interactive storyboa...

Mandatory keyskills : Python Programming Strong proficiency is essential for building and deploying ML models. Cloud Platforms (Azure, GCP, AWS) – Hands-on experience with at least one major cloud provider. Linux & Docker – Solid understanding of containerization and operating systems for scalable deployment. ML/Ops Tools (e.g., Azure ML) – Experience in deploying and managing machine learning models in production.

Hello Candidate, Greetings from Hungry Bird IT Consulting Services Pvt Ltd. We are hiring Senior AI Infrastructure Management Engineer for our client. Job Title: Senior AI Infrastructure Management Engineer Location: Hyderabad Job Type: Full-Time Work Mode: Hybrid E xperience Required: 6+ Years Job Summary: We are seeking a highly skilled Senior AI Infrastructure Management Engineer with expertise in Azure , AWS , and AI/ML deployment environments. This role demands deep technical knowledge of Linux , DevOps practices , cloud architecture , and AI/ML operations (MLOps/AIOps) . The ideal candidate will be responsible for architecting, deploying, and maintaining scalable and secure infrastruct...

dunnhumby is the global leader in Customer Data Science, empowering businesses everywhere to compete and thrive in the modern data-driven economy. We always put the Customer First. Our mission: to enable businesses to grow and reimagine themselves by becoming advocates and champions for their Customers. With deep heritage and expertise in retail one of the world’s most competitive markets, with a deluge of multi-dimensional data – dunnhumby today enables businesses all over the world, across industries, to be Customer First. dunnhumby employs nearly 2,500 experts in offices throughout Europe, Asia, Africa, and the Americas working for transformative, iconic brands such as Tesco, Coca-Cola, M...

About the Role: Grade Level (for internal use): 09 The Team As a member of the EDO, Collection Platforms & AI Cognitive Engineering team you will build and maintain enterprisescale data extraction, automation, and ML model deployment pipelines that power data sourcing and information retrieval solutions for S&P Global. You will learn to design resilient, production-ready systems in an AWS-based ecosystem while leading by example in a highly engaging, global environment that encourages thoughtful risk-taking and self-initiative. Whats in it for you: Be part of a global company and deliver solutions at enterprise scale Collaborate with a hands-on, technically strong team (including leadership)...

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...

Project description New settlements and confirmation system for FX trades. Responsibilities We are seeking an AI-ML Tech Engineer who has a minimum of 8+ years of strong background in machine learning, data science, and software engineering. As a Machine Learning Engineer, you will develop and deploy machine learning models, work with large datasets, and collaborate with cross-functional teams to solve real-world problems. Skills Must have Proficient in building ML (Machine Learning) & NLP (Natural Language Processing) solutions using common ML libraries and frameworks. Proficient with Python language and worked on various ML toolkits like TensorFlow, PyTorch, Keras, Scikit Learn. Theoretica...

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Devel...

Greeting From BMW Techworks !! Experience: 3 to 8 Years Location: Bangalore, Pune Notice period: immediate to 60days Job Description :- We are seeking a skilled Software Engineer with expertise in AWS cloud technologies to design, develop, and deploy scalable applications using core AWS services. Familiarity with computer vision/deep learning is a plus and will enhance your ability to contribute to cutting edge projects in Automated Driving technologies. Key Responsibilities: Design, develop, and maintain scalable, high-performance applications using AWS services such as EC2, S3, Lambda, RDS, DynamoDB, Batch and ECS/EKS. Monitor and optimize application performance using AWS tools like Cloud...

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Collaborate with sales, pre-sales &consulting team to assist in creating solutions and propositions for proactive demand generation ii. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for recruitment, joint research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Devel...

Role Purpose The purpose of the role is to define, architect and lead delivery of machine learning and AI solutions. Do 1. Demand generation through support in Solution development a. Support Go-To-Market strategy i. Contribute to development solutions, proof of concepts aligned to key offerings to enable solution led sales b. Collaborate with different colleges and institutes for research initiatives and provide data science courses 2. Revenue generation through Building & operationalizing Machine Learning, Deep Learning solutions a. Develop Machine Learning / Deep learning models for decision augmentation or for automation solutions b. Collaborate with ML Engineers, Data engineers and IT t...