232 Ml Pipelines Jobs - Page 4

You will be responsible for building the machine learning production system (MLOps) to help large companies transition into AI-driven organizations. As an MLOps Engineer, you will collaborate with Data Scientists and Data Engineers to deploy and operate advanced analytics machine learning models. Your key responsibilities will include: - Enabling model tracking, experimentation, and automation - Developing scalable ML pipelines - Building MLOps components using Model Repository (e.g., MLFlow, Kubeflow Model Registry) and Machine Learning Services (e.g., Kubeflow, DataRobot, HopsWorks, Dataiku) - Working across all phases of the Model development life cycle to build MLOps components - Buildin...

About The Role Project Role : Enterprise Technology Architect Project Role Description : Architect complex end-to-end IT solutions across the enterprise. Apply the latest technology and industry expertise to create better products and experiences. Must have skills : Data Consulting Good to have skills : NA Minimum 7.5 year of experience is required Educational Qualification : 15 years full time education Summary :Deliver AI/ML/GenAI solutions in engineering programs with focus on design automation and PLM data.Roles & Responsibilities:Build ML/GenAI solutions for CAD/PLM auto-classification.Implement copilots inside PLM environments.Automate defect/rework prediction.Collaborate with architec...

We are seeking a Machine Learning Engineer with strong expertise in traditional ML algorithms and statistical modeling techniques. The role involves developing, training, testing, and deploying ML models to solve business problems, improve decision-making, and optimize processes. The ideal candidate should have a solid background in mathematics, statistics, and programming, with hands-on experience in applying classical ML techniques rather than relying solely on deep learning frameworks. Key Responsibilities: Design, develop, and implement machine learning models using traditional algorithms (e.g., regression, SVM, decision trees, ensemble methods, clustering, time series forecasting). Perf...

As a Machine Learning Engineer, you will be responsible for designing, developing, and deploying scalable ML solutions using GCP and Vertex AI. You will work closely with data scientists, engineers, and product teams to operationalize models and manage the full ML lifecycle. Key Responsibilities: Model Development & Deployment: Build, train, and optimize ML models using Vertex AI (AutoML, custom training jobs, Workbench). Deploy models to production using Vertex AI endpoints and integrate with APIs or downstream systems. ML Pipelines & MLOps: Design and implement scalable ML pipelines using Vertex AI Pipelines, Kubeflow, and Cloud Functions. Apply CI/CD practices using Cloud Build, GitHub Ac...

!!! Hiring !! Soft skills Combination of business focus, analytical and problem solving skills in order to quickly define a data-driven solution within different initiatives Ability to work within a team and with a proactive attitude Ability to communicate and popularize technical topics Main skills - Programming in Python (Numpy, Pandas, Scikit-learn, ) - Mastery of basic Devops tools (Versionning Git, Docker, CI/CD concepts e.g. Gitlab CI framework) - Mastery of ML Ops and ML Engineering frameworks (Experiment trackers e.g. MLFlow, Orchestrators – e.g. Airflow, Kubeflow, Sagemaker) - Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neura...

Responsibilities: * Develop computer vision solutions using Python, PyTorch or TensorFlow. * Collaborate with cross-functional teams on ML pipeline development and deployment.

So, what’s t he r ole all about? We are seeking an experienced AI Architect who is not only capable of strategic thinking but also enthusiastic about hands-on coding and contributing directly to both proof-of-concept (POC) and production-grade AI projects. The ideal candidate will play a key role in mentoring team members, establishing ethical and responsible AI practices, and making critical decisions around AI deployment strategies. A strong background in deploying AI solutions on cloud platforms such as Azure or AWS is essential, along with deep expertise in building secure, compliant data and machine learning pipelines . This role demands a proactive leader who can bridge the gap between...

HOW MIGHT YOU DEFY IMAGINATION If you feel like youre part of something bigger, its because you are At Amgen, our shared mission?to serve patients?drives all that we do It is key to our becoming one of the worlds leading biotechnology companies We are global collaborators who achieve together?researching, manufacturing, and delivering ever-better products that reach over 10 million patients worldwide Its time for a career you can be proud of Live | What you will do Build, test, and maintain reusable components for ML pipelines and data science use cases in collaboration with senior engineers and data scientists Develop model tracking, versioning, and deployment workflows using MLflow and Dat...

Project Role : AI / ML Engineer Project Role Description : Develops applications and systems that utilize AI tools, Cloud AI services, with proper cloud or on-prem application pipeline with production ready quality. Be able to apply GenAI models as part of the solution. Could also include but not limited to deep learning, neural networks, chatbots, image processing. Must have skills : Machine Learning Operations Good to have skills : NAMinimum 7.5 year(s) of experience is required Educational Qualification : 15 years full time education Summary :As an Machine Learning Engineer/MLOps Expert, you will engage in the operationalization of Machine Learning Models that leverage artificial intellig...

Job Description We are looking for an experienced Machine Learning Engineer who can build, deploy, and maintain end-to-end ML pipelines in real-world production environments. The candidate will collaborate with cross-functional teams to define business problems, design machine learning solutions, and support model deployment and monitoring in the cloud. Key Responsibilities Collaborate with business stakeholders to understand requirements and translate them into ML problem statements. Develop and deploy machine learning and deep learning models using frameworks such as TensorFlow , PyTorch , or Keras . Build end-to-end ML pipelines from data ingestion, preprocessing, feature engineering to t...

Role & Responsibilities Develop and maintain scalable Django-based APIs and AI-powered applications. Integrate large language models (LLMs) and other machine learning services into our core products. Design, build, and manage AI/ML pipelines for data processing, model training, and deployment. Build responsive frontends using modern frameworks like React or Angular . Deploy and manage applications and models on cloud platforms (AWS, GCP, or Azure). Optimize databases (PostgreSQL, MongoDB) to support high-throughput AI services. Ensure the security, scalability, and performance of both the web and AI components of the stack. Preferred Candidate Profile 3+ years of professional experience in D...

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...

Job Title: MLOps Engineer Location: Remote / Pan India,Delhi NCR,Bengaluru,Chennai,Pune,Kolkata,Ahmedabad, Mumbai, Hyderabad iSource Services is hiring for one of their client for the position of MLOps Engineer. About the Role: The ML Ops Engineer plays a critical role in the development, automation, and deployment of Machine Learning (ML) and Generative AI (GenAI) pipelines across AWS cloud environments. This hands-on role emphasizes building reproducible workflows, integrating observability tools, and enabling efficient, scalable model delivery. The position supports AI systems deployed in banking environments, where resilience and reliability are paramount. Core Requirements (In Order of ...

This role offers the opportunity to leverage your cloud-native deployment skills and experience with modern AI platforms to build scalable ML pipelines, LLM-based applications, and intelligent agent frameworks. You will play a key role in accelerating the delivery of innovative solutions for telecom, enterprise, and next-generation autonomous networks. If you thrive in a challenging and rewarding environment, we encourage you to apply. You have: Bachelor's/Master's degree in computer science, Data Engineering, AI/ML, or related field. 10+ years in AI/ML engineering, with 5+ years focused on MLOps. Proficient in Python, PyTorch, TensorFlow, Scikit-learn, and SQL. Experience with MLOps pipelin...

About the Role: We are hiring a Senior Data Engineer with strong expertise in Palantir Foundry or Gotham to lead the design, development, and optimization of data engineering solutions across large-scale enterprise environments. The ideal candidate will have deep experience building secure, high-performance data pipelines using Python, ETL/ELT practices, distributed computing frameworks, and cloud platforms ( AWS ,Azure ,GCP)while working closely with DevOps, analytics, and business teams to enable data-driven decisions. Key Responsibilities: Architect, build, and optimize large-scale ETL/ELT pipelines using Palantir Foundry/Gotham . Integrate diverse data sources including SQL , NoSQL , API...

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...

This role offers the opportunity to leverage your cloud-native deployment skills and experience with modern AI platforms to build scalable ML pipelines, LLM-based applications, and intelligent agent frameworks. You will play a key role in accelerating the delivery of innovative solutions for telecom, enterprise, and next-generation autonomous networks. If you thrive in a challenging and rewarding environment, we encourage you to apply. You have: Bachelor's/Master's degree in computer science, Data Engineering, AI/ML, or related field. 10+ years in AI/ML engineering, with 5+ years focused on MLOps. Proficient in Python, PyTorch, TensorFlow, Scikit-learn, and SQL. Experience with MLOps pipelin...

Role & responsibilities Collaborate with business stakeholders to understand requirements and translate them into ML problem statements. Develop and deploy machine learning and deep learning models using frameworks such as TensorFlow , PyTorch , or Keras . Build end-to-end ML pipelines from data ingestion, preprocessing, feature engineering to training and deployment. Work with structured and unstructured data , applying advanced data preprocessing and augmentation techniques. Integrate ML models into scalable backend systems or APIs. Monitor model performance and design model evaluation/operationalization metrics . Deployment of models using cloud platforms such as AWS Sagemaker , Azure ML ...

Role & responsibilities Collaborate with business stakeholders to understand requirements and translate them into ML problem statements. Develop and deploy machine learning and deep learning models using frameworks such as TensorFlow , PyTorch , or Keras . Build end-to-end ML pipelines from data ingestion, preprocessing, feature engineering to training and deployment. Work with structured and unstructured data , applying advanced data preprocessing and augmentation techniques. Integrate ML models into scalable backend systems or APIs. Monitor model performance and design model evaluation/operationalization metrics . Deployment of models using cloud platforms such as AWS Sagemaker , Azure ML ...

This role offers the opportunity to leverage your cloud-native deployment skills and experience with modern AI platforms to build scalable ML pipelines, LLM-based applications, and intelligent agent frameworks. You will play a key role in accelerating the delivery of innovative solutions for telecom, enterprise, and next-generation autonomous networks. If you thrive in a challenging and rewarding environment, we encourage you to apply. You have: Bachelor's/Master's degree in computer science, Data Engineering, AI/ML, or related field. 10+ years in AI/ML engineering, with 5+ years focused on MLOps. Proficient in Python, PyTorch, TensorFlow, Scikit-learn, and SQL. Experience with MLOps pipelin...

Role Overview;- We are looking for a skilled and motivated Machine Learning Engineer / Data Scientist to join our team. The ideal candidate should have a strong foundation in machine learning and deep learning, with experience in building end-to-end ML pipelines and hybrid modeling approaches that incorporate both physics-based simulations and data-driven insights. You will work on high-impact projects involving time series forecasting, predictive modeling, and system simulation to support data-driven decision-making. Role & Responsibilities :- Design, train, and evaluate machine learning and deep learning models for regression, classification, and forecasting tasks. Build and maintain end-t...

As a candidate for the position, you will be expected to have the following Educational Requirements: - Bachelor of Engineering/Bachelor of Technology in any stream with consistent academic track record. - Bachelor's degree in a quantitative discipline (e.g., Operation Research, Statistics, Mathematics) or significant relevant coursework with consistent academic track record. Additional Academic Qualification (good to have): - Masters in any area related to Science, Operation Research, Mathematics and Statistics with consistent academic track record. - PhD in any stream. Your key responsibilities in this role will include: - Understanding the requirements from the business and translating th...

About the Team Our Data Science team is the Avengers to Meeshos S.H.I.E.L.D ???. And why not? We are the ones who assemble during the toughest challenges and devise creative solutions, building intelligent systems for millions of our users looking at a thousand different categories of products. Weve barely scratched the surface, and have amazing challenges in charting the future of commerce for Bharat. Our typical day involves dealing with fraud detection, inventory optimisation, and platform vernacularisation. As Lead Data Scientist, you will navigate uncharted territories with us, discovering new paths to creating solutions for our users.?? You will be at the forefront of interesting chall...

As a Global Product Lead at MiQ, a global programmatic media partner, you will play a crucial role in leading and expanding a unified Data Management and LLMOps framework. Your responsibilities will include: - Leading and expanding a unified Data Management and LLMOps framework across various functions such as engineering, analytics, data science, and ad operations. - Architecting and managing automated data pipelines for onboarding, cleansing, and processing structured and unstructured data using advanced AI/agentic automation. - Overseeing the adoption and execution of Agentic AI in data workflows, defining and scaling LLMOps best practices, and ensuring seamless orchestration of AI models...