5 Mlops Frameworks Jobs

Solution Architect (India) Work Mode: Remote/ Hybrid Required exp: 10+ years Shift timing: Minimum 4 hours overlap required with US time Role Summary: The Solution Architect is responsible for designing robust, scalable, and high- performance AI and data-driven systems that align with enterprise goals. This role serves as a critical technical leaderbridging AI/ML, data engineering, ETL, cloud architecture, and application development. The ideal candidate will have deep experience across traditional and generative AI, including Retrieval- Augmented Generation (RAG) and agentic AI systems, along with strong fundamentals in data science, modern cloud platforms, and full-stack integration. Key Responsibilities: ? Design and own the end-to-end architecture of intelligent systems including data ingestion (ETL/ELT), transformation, storage, modeling, inferencing, and reporting. ? Architect GenAI-powered applications using LLMs, vector databases, and RAG pipelines; Agentic Workflow, integrate with enterprise knowledge graphs and document repositories. ? Lead the design and deployment of agentic AI systems that can plan, reason, and interact autonomously within business workflows. ? Collaborate with cross-functional teams including data scientists, data engineers, MLOps, and frontend/backend developers to deliver scalable and maintainable solutions. ? Define patterns and best practices for traditional ML and GenAI projects, covering model governance, explainability, reusability, and lifecycle management. ? Ensure seamless integration of ML/AI systems via RESTful APIs with frontend interfaces (e.g., dashboards, portals) and backend systems (e.g., CRMs, ERPs). ? Architect multi-cloud or hybrid cloud AI solutions, leveraging services from AWS, Azure, or GCP for scalable compute, storage, orchestration, and deployment. ? Provide technical oversight for data pipelines (batch and real-time), data lakes, and ETL frameworks ensuring secure and governed data movement. ? Conduct architecture reviews, mentor engineering teams, and drive design standards for AI/ML, data engineering, and software integration. Qualifications : ? Bachelors or Masters degree in Computer Science, Engineering, or a related field. ? 10+ years of experience in software architecture, including at least 4 years in AI/ML-focused roles. Required Skills: ? Expertise in machine learning (regression, classification, clustering), deep learning (CNNs, RNNs, transformers), and NLP. ? Experience with Generative AI frameworks and services (e.g., OpenAI, LangChain, Azure OpenAI, Amazon Bedrock). ? Strong hands-on Python skills, with experience in libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch. ? Proficiency in RESTful API development and integration with frontend components (React, Angular, or similar is a plus). ? Deep experience in ETL/ELT processes using tools like Apache Airflow, Azure Data Factory, or AWS Glue. ? Strong knowledge of cloud-native architecture and AI/ML services on either one of the cloud AWS, Azure, or GCP. ? Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and semantic search patterns.? Experience in deploying and managing ML models with MLOps frameworks (MLflow, Kubeflow). ? Understanding of microservices architecture, API gateways, and container orchestration (Docker, Kubernetes). ? Having forntend exp is good to have. Show more Show less

As a Data Scientist at Rockwell Automation, you will be part of an analytics team working alongside engineers, product managers, and partners to drive AI-powered features for the platform. Collaborating with process engineers and operations leads, you will be responsible for developing predictive-maintenance models, enhancing throughput and yield, and implementing cost-saving strategies across manufacturing lines. Your role will involve managing end-to-end projects, including scoping data-collection architectures, prototyping machine-learning solutions, deploying models into the IIoT platform, and establishing real-time monitoring dashboards. Additionally, you will mentor junior analysts, engage in pilot projects with R&D, and contribute to shaping the roadmap for advanced-analytics capabilities. If you enjoy tackling complex industrial challenges, translating diverse data sources into actionable business insights, and evolving as a trusted analytics partner for clients, Rockwell Automation offers an environment where you can advance both your career and your clients" success. Reporting to the Lead Sr Solution Architect, you will be based at our Electronics City office in Bengaluru, following a hybrid work model. Your Responsibilities: - Leading end-to-end data-science projects by defining hypotheses, designing experiments, building features, training models, and deploying them in production. - Collaborating with Engineering to integrate ML services into the microservices architecture and with Marketing for A/B testing data-driven campaigns. - Creating scalable ETL pipelines and designing data schemas to support analytics and modeling at scale. - Developing monitoring dashboards and automated retraining workflows to ensure model accuracy. Essential Qualifications: - 6-10 years of experience in Python, SQL, Pandas, scikit-learn, and PySpark. - Proficiency in supervised and unsupervised ML techniques, advanced statistics, computer vision, and generative-AI projects. - Familiarity with Docker, Kubernetes, cloud ML platforms, and communicating data insights effectively. Preferred Qualifications: - Familiarity with BI tools, MLOps frameworks, FastAPI, and Linux environments. What We Offer: - Comprehensive benefits package including mindfulness programs, volunteer time off, donation matching, employee assistance programs, wellbeing initiatives, and professional development resources. - Commitment to fostering a diverse, inclusive, and authentic workplace. At Rockwell Automation, we value diversity and encourage candidates who are interested in the role to apply even if their experience does not align perfectly with every qualification listed. You might be the ideal fit for this position or other opportunities within the organization.,

As a Data Scientist specializing in Generative AI & ML Engineering, your primary responsibility will be to research and develop AI algorithms and models. You will be tasked with analyzing data, constructing predictive models, and employing machine learning techniques to address intricate problems. Your proficiency should encompass a range of skills including proficiency in languages/frameworks such as Fast API and Azure UI Search API (React), as well as expertise in databases and ETL tools like Cosmos DB and Data Factory Data Bricks. In addition, you should have a strong command of Python and R, familiarity with Azure Cloud Basics and Gitlab Pipeline, and experience in deploying AI solutions end-to-end. In addition to your proficient skills, you are expected to possess expert-level knowledge in areas such as Azure Open AI, Open AI GPT Family of models, and Azure Storage Account. Your expertise should extend to machine learning algorithms, deep learning frameworks like TensorFlow and PyTorch, and a solid foundation in mathematics including linear algebra, calculus, probability, and statistics. Furthermore, your role will require proficiency in data analysis tools such as Pandas, NumPy, and SQL, as well as strong statistical and probabilistic modeling skills. Experience with data visualization tools like Matplotlib, Seaborn, and Tableau, along with knowledge of big data technologies like Spark and Hive, will be essential for success in this position. Overall, your experience in AI-driven analytics and decision-making systems, coupled with your ability to develop and deploy AI frameworks and models, will be critical in delivering effective solutions to complex challenges.,

Role & responsibilities Proficient: Languages/Framework: Fast API, Azure UI Search API (React) tabases and ETL: Cosmos DB (API for MongoDB), Data Factory Data Bricks Proficiency in Python and R Cloud: Azure Cloud Basics (Azure DevOps) Gitlab: Gitlab Pipeline o Ansible and REX: Rex Deployment Data Science: Prompt Engineering + Modern Testing Data mining and cleaning ML (Supervised/unsupervised learning) NLP techniques, knowledge of Deep Learning techniques include RNN, transformers End-to-end AI solution delivery AI integration and deployment AI frameworks (PyTorch) MLOps frameworks Model deployment processes Data pipeline monitoring Expert: (in addition to proficient skills) Languages/Framework: Azure Open AI Data Science: Open AI GPT Family of models 4o/4/3, Embeddings + Vector Search Databases and ETL: Azure Storage Account Expertise in machine learning algorithms (supervised, unsupervised, reinforcement learning) Proficiency in deep learning frameworks (TensorFlow, PyTorch) Strong mathematical foundation (linear algebra, calculus, probability, statistics) Research methodology and experimental design Proficiency in data analysis tools (Pandas, NumPy, SQL) Strong statistical and probabilistic modelling skills Data visualization skills (Matplotlib, Seaborn, Tableau) Knowledge of big data technologies (Spark, Hive) Experience with AI-driven analytics and decision-making systems Note: ***Notice Period should not be more than 10-15 days. ***

About the role You will have a vital role in developing complex solutions and deploying transformative data products. You will work in a team responsible for building Analytical insights, recommendation engines and boutique algorithms. You will identify new areas to apply data science to improve business performance. As a digital marketplace with millions of reviews and insights from our clients, there are limitless opportunities to apply your skills in data science. You will cover a broad and evolving set of responsibilities as you build data science capabilities at RCD versatility, adaptability, and self-sufficiency will be critical to success. As a member of the Gartner family, you will have access to industry-leading research on analytics and data science solutions to help you deliver more engaging and relevant content for software buyers and improve the volume and quality of buyer leads for software sellers. What will you do: Research & Development Research, design, and implement advanced machine learning (ML) and data algorithms, with a focus on analyzing text data and extracting actionable insights. Stay current with the latest advancements in large language models (LLMs), generative AI (GenAI), and related technology trends to ensure the adoption of cutting-edge techniques. ML Models Development & Optimization Build and deploy ML models that facilitate effective matching of buyers to relevant content, enhancing the buyers journey. Fine-tune pre-trained language models for specific business use cases, optimizing for accuracy, performance, and domain relevance. End-to-End Solution Delivery Lead the end-to-end development lifecycle of ML solutions, from rapid prototyping to full-scale productization. Ensure seamless integration of ML solutions into existing systems and workflows, maintaining high standards of reliability and scalability. Collaboration & Stakeholder Engagement Work closely with Engineering and Product Management teams to align on and execute the data science roadmap. Gather and analyze requirements from stakeholders, ensuring solutions are tailored to business needs and deliver measurable value. Data Infrastructure & Solution Design Play a hands-on role in the design and implementation of robust data warehousing solutions to support scalable analytics and ML initiatives. Ensure data quality, integrity, and security throughout the data lifecycle. Agile Delivery & Continuous Improvement Participate in Agile Scrum ceremonies and processes, driving the iterative delivery of high-quality ML solutions. Lead efforts in testing, validation, and post-rollout continuous improvement to maximize business impact and solution effectiveness. What you’ll need Bachelor’s degree in computer science, Information Systems, or a related field, or equivalent hands-on experience in software development. 6-8 years of professional experience in software engineering and/or data warehousing, with a proven track record of delivering solutions in Agile Scrum environments. Proficiency in Python and a solid understanding of Object-Oriented Programming (OOP) principles. Demonstrated expertise in machine learning models , with hands-on experience working with AWS cloud services and Cassandra databases. Familiarity with AWS ML tools and best practices for deploying and managing scalable machine learning solutions in the cloud. Must be proficient in: Machine learning extraction mechanisms using AWS , including operationalizing end-to-end ML solutions in the cloud. Entity-Relationship (ER) modeling and expertise in T-SQL for effective data modeling and management. SQL query and dataset optimization to ensure high performance and scalability. Experience with version control systems (e.g., Git, SVN) for collaborative software development. Good to have skills: Generative AI techniques , including tokenization, word embeddings, and advanced prompting strategies. Solid understanding of foundational concepts such as Transformers and Self-Attention mechanisms underpinning large language models (LLMs). Strong proficiency in querying languages such as SQL, and hands-on experience with data transformation packages including Python’s Pandas, Polars, or Dask. Proficient in using data visualization libraries such as ggplot2, Plotly, and Matplotlib to create insightful and actionable visual representations. Familiarity with dashboard and reporting tools for effective data presentation and business intelligence. Experience working with cloud computing platforms and tools, such as AWS and Azure, for scalable application and data solution deployment. Who you are: A strong, passionate, empathetic engineer, who can work is able to work collaboratively with senior leadership, peers, and project team to deliver solutions on time, within budget, keeping the morale high Self-starter, with a demonstrated ability to learn beyond formal training with a strong aptitude for delivering quality products Passionate about learning new technologies Proficiency in project tracking tools like Jira for effective project management and delivery tracking. Strong ability to interpret and manage client expectations , proactively identifying and resolving issues that could impact project delivery. Excellent interpersonal skills with a proven ability to work effectively within a matrixed and distributed team environment. Demonstrated problem-solving skills and the ability to work both independently and collaboratively in a fast-paced setting. Exceptional organizational and analytical skills , with keen attention to detail and the ability to maintain a strategic, big-picture perspective. What we offer: In addition to an outstanding work environment with rapid advancement potential, Gartner associates enjoy exceptional compensation and benefits, including: An upbeat, positive culture. Integrity, objectivity, collaboration, results and a no-limits mindset are central to our values Limitless growth. We work with you to help you meet your goals and advance within the company Encouragement to be innovative and challenge status quo Exposure to industry leading training and development Performance based recognition and rewards