7 Mlops Platforms Jobs

As a Staff Software Engineer at Qualcomm India Private Limited, with a minimum of 10-15 years of experience in Electronic Design Automation (EDA), your role will involve designing, deploying, and scaling software platforms that integrate Machine Learning with semiconductor design, aimed at revolutionizing chip development workflows. **Key Responsibilities:** - Design and develop end-to-end ML-integrated EDA software platforms for scalability, performance, and adaptability. - Establish software development processes incorporating best practices and agility. - Create advanced algorithms for automation and optimization in EDA flows. - Engineer reliable and scalable data pipelines to support ML model development. - Implement full-stack deployment strategies for ML applications in diverse environments. - Execute system integration and testing to ensure seamless operability across large systems. - Ensure reliability and scalability of large system deployments on high-performance compute platforms. **Required Skills & Experience:** - Experience in software development focusing on architecture for ML and EDA tools. - Proficiency in Python, C++, and frameworks like TensorFlow, PyTorch, or Scikit-learn. - Familiarity with CI/CD tools (e.g., GitLab, Jenkins) and MLOps platforms (e.g., MLflow, Kubeflow). - Strong communication and leadership skills with a history of cross-functional collaboration. **Preferred Qualifications:** - MS or PhD in Computer Science, Electrical Engineering, or related field. - Expertise in advanced ML techniques such as graph neural networks or reinforcement learning applied to EDA. - Contributions to open-source projects, patents, or technical publications related to ML-driven design automation. Qualcomm is an equal opportunity employer and is committed to providing reasonable accommodations for individuals with disabilities during the application/hiring process. If you require an accommodation, you can email disability-accommodations@qualcomm.com or call Qualcomm's toll-free number. Additionally, Qualcomm expects its employees to adhere to all relevant policies and procedures, including those concerning the protection of confidential information. Please note that Qualcomm's Careers Site is exclusively for individuals seeking employment at Qualcomm, and staffing agencies are not authorized to use the site for submissions. Unsolicited resumes or applications from agencies will not be accepted. For further information about this role, please reach out to Qualcomm Careers.,

As a Staff Software Developer specializing in Machine Learning for EDA Systems at Qualcomm India Private Limited, you will play a crucial role in designing and implementing cutting-edge machine learning techniques in the realm of Electronic Design Automation (EDA). Your primary responsibilities will revolve around leading software development initiatives, guiding a team of engineers and ML practitioners, and ensuring the seamless integration of ML into semiconductor design workflows. Below are the key details of the job: **Role Overview:** You will be responsible for designing and developing end-to-end ML-integrated EDA software platforms, leading a team of engineers, refining software development processes, spearheading advanced algorithm design, and overseeing deployment strategies. **Key Responsibilities:** - Design and develop ML-integrated EDA software platforms for scale, performance, and adaptability. - Guide and mentor a team of software engineers and ML practitioners. - Own and refine software development processes and embed best practices. - Spearhead advanced algorithm design for automation and optimization in EDA flows. - Engineer reliable and scalable data pipelines for ML model development. - Oversee full-stack deployment strategies for ML applications. - Establish and maintain comprehensive ML Ops infrastructure. - Experience in system integration and testing initiatives. - Manage CI/CD pipelines and ensure system scalability. **Required Skills & Experience:** - 8+ years of software development experience with a focus on ML and EDA tools. - Proficiency in Python, C++, and frameworks like TensorFlow, PyTorch, or Scikit-learn. - Familiarity with CI/CD tools and MLOps platforms. - Deep knowledge of EDA tools and flows. - Skilled in data engineering and cloud/on-prem infrastructures. - Strong communication and leadership skills. **Preferred Qualifications:** - MS or PhD in Computer Science, Electrical Engineering, or related field. - Expertise in advanced ML techniques applied to EDA. - Contributions to open-source, patents, or technical publications related to ML-driven design automation. Please note that Qualcomm is an equal opportunity employer and is committed to providing accessible processes for individuals with disabilities. For further information about this role, please contact Qualcomm Careers.,

Position Title: AI & Industry 4.0 Transformation Lead Location: Gurgaon (Head Office) [Best Group] To Apply: https://forms.office.com/r/FByEwfL2mU About Best Group Best Group is a dynamic conglomerate with over five decades of excellence, specializing in: Manufacturing: Designing and engineering automotive and defense solutions that lead the industry. Future Factory Solutions: Creating disruptive and intelligent systems to drive the automotive industry&aposs next frontier. Education: Fostering a learning ecosystem that equips learners for an accelerating, tech-driven future. Our ethos is rooted in ethical innovation, sustainability, and building a legacy with shared values, societal growth, and world-class quality. How Youll Make an Impact Architect Transformation: Define and build AI frameworks that turn industrial processes into intelligent, autonomous systems. Pioneer Autonomy: Lead development of real-time, adaptive AI agents in manufacturing environments. Bridge Research & Reality: Translate cutting-edge AI methods into deployable, industrial-grade solutions. Own the AI Lifecycle: From data intake to deployment, ensure models are scalable, reliable, and future-ready. Lead with Vision: Inspire and grow a team of AI innovators committed to redefining industry norms. Champion Integration: Collaborate across IoT, product, and business teams to deliver cohesive and transformative systems. Ensure Governance & Scalability: Uphold governance, traceability, and compliance while scaling AI operations. What We&aposre Looking For Masters or PhD in AI/ML or related discipline. 5+ years in enterprise AI/ML. Expertise in: AI/ML architecture & predictive modeling MLOps platforms (e.g., MLflow, Kubeflow, SageMaker, Vertex AI) Industrial-scale data processing Proven background in: Low-code enterprise solution delivery (mandatory) Full product lifecycle leadership (mandatory) Building and leading AI/ML teams (mandatory) IIoT or Industry 4.0 environments (highly desirable) Why Join Best Group Be at the forefront of Indias Industry 4.0 revolution . Lead AI initiatives that transform manufacturing worldwide . Join a values-driven team committed to sustainability, innovation, and growth . Show more Show less

As a computer vision support engineer with 5-8 years of experience, you will be part of the "run operations" team at Colruyt Group's innovation hub, Smart Technics, based in Hyderabad, India. Your role involves maintaining, supporting, and enhancing applications and ICT systems that are utilized by Colruyt Group's business partners and external customers. Smart Technics focuses on robotics, engineering, artificial intelligence, and automation projects with the aim of setting new standards in retail and logistics over the next decade. This role offers exposure to diverse cutting-edge products, providing an excellent learning experience and growth opportunities. Your responsibilities include providing second-line technical support for Smart Technics products that leverage computer vision technology. You will support end-to-end product functionalities, such as camera systems, GPU compute platforms, MLOps platforms, AI models, and software applications, collaborating with internal and external experts and support teams. In addition to incident resolution, you will be responsible for maintaining applications, monitoring system stability, managing the application life cycle, and ensuring compliance with IT service management processes. Collaboration with the Service Delivery Manager is essential for application lifecycle management and SLA monitoring. You will contribute to feature development, continuous product improvement, and the optimization of AI models. Proactively identifying areas for scalability, maintainability, and supportability enhancements is key to ensuring product quality and customer satisfaction. Your role also involves assisting in the transition from minimum viable product (MVP) to robust, supportable solutions. Your profile should include a background in computer science or engineering, proficiency in computer vision technologies, and experience in application lifecycle management. Knowledge of ITIL methodology and/or IT4IT is advantageous. Problem-solving skills, customer orientation, clear communication, analytical thinking, and proficiency in English are essential for this role. In return, we offer a dynamic and innovative work environment that provides continuous learning opportunities and a clear growth trajectory.,

About Anyscale: At Anyscale, the mission is to democratize distributed computing and make it accessible to software developers of all skill levels. The company is commercializing Ray, a popular open-source project that is creating an ecosystem of libraries for scalable machine learning. Ray is utilized by companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more to accelerate the progress of AI applications. Anyscale is focused on building the best platform to run Ray, enabling any developer or data scientist to scale an ML application from their laptop to the cluster without the need to be a distributed systems expert. Backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date. About The Role: The primary role is to serve as a technical advisor and champion for Anyscale customers with expertise in infrastructure, cloud management, K8, etc. Responsibilities include playing a crucial role in the customers" post-sale journey, helping them to onboard, adopt and grow on Anyscale, troubleshooting and resolving open customer tickets, and driving consumption. This role requires close coordination with engineering teams to debug complex issues. The position offers an exciting opportunity for those who are technically curious and passionate about ML/AI, LLM, vLLM, and the role of AI in next-generation applications. Responsibilities Include: - Being a solutions architect, technical advisor, and internal champion for key customers to successfully onboard and adopt the Anyscale platform - Owning customer issues end-to-end, from troubleshooting, escalations, and resolution - Participating in the follow-the-sun customer support model to ensure continuity in resolving high-priority tickets - Managing current workload state of key customers and identifying new workloads to drive account expansion - Contributing towards the improvement of internal tools, documentation of playbooks, guides, and best practices based on observed patterns - Providing feedback and collaborating cross-functionally with product and engineering teams to address customer issues and improve the product experience - Building and maintaining strong relationships with technical stakeholders within customer accounts Qualifications: - 5+ years of experience in a customer-facing technical role with 2+ years in a dynamic, fast-paced, startup-like environment - Strong organizational skills and ability to manage multiple customer needs simultaneously - Proficiency in deploying and resolving issues within container orchestration platforms (such as Kubernetes) and working with infrastructure as code tools (such as Terraform) - Hands-on experience with major cloud platforms (AWS, GCP, or Azure) - Knowledge of Observability tools (e.g., Grafana) - Excellent communication and interpersonal skills - Strong sense of ownership, self-motivation, and eagerness to acquire new skills - Willingness to uplevel the knowledge and skills of peers through mentorship, training, and shadowing Bonus Qualifications: - Experience with Ray - Knowledge of MLOps platforms in support of ML/AI, Data Engineering, and Data Science teams - Familiarity with container orchestration platforms (e.g., Kubernetes), infrastructure as code (e.g., Terraform), CI/CD tools (e.g., Github Actions) - Knowledge of training, fine-tuning, and inference/serving of LLMs Compensation: Anyscale takes a market-based approach to compensation, being data-driven, transparent, and consistent. The target salary for this role may be adjusted over time based on market data changes. Anyscale Inc. is an E-Verify company, and you may review the Notice of E-Verify Participation and the Right to Work posters in English and Spanish.,

You should have at least 2-7 years of experience in software engineering and ML development. Proficiency in Python and ML libraries like Scikit-learn, TensorFlow, or PyTorch is essential. Your responsibilities will include building and evaluating models, data preprocessing, and feature engineering. It is important to have a good understanding of REST APIs, Docker, Git, and CI/CD tools. A strong foundation in software engineering principles such as data structures, algorithms, and design patterns is required. Hands-on experience with MLOps platforms like MLflow, TFX, Airflow, and Kubeflow is preferred. Exposure to NLP, large language models (LLMs), or computer vision projects will be beneficial for this role. Experience with cloud platforms such as AWS, GCP, and Azure, as well as managed ML services, is a plus. Any contributions to open-source ML libraries or participation in ML competitions like Kaggle or DrivenData will be considered an advantage.,

As a Senior Systems Engineer specializing in Data DevOps/MLOps, you will play a crucial role in our team by leveraging your expertise in data engineering, automation for data pipelines, and operationalizing machine learning models. This position requires a collaborative professional who can design, deploy, and manage CI/CD pipelines for data integration and machine learning model deployment. You will be responsible for building and maintaining infrastructure for data processing and model training using cloud-native tools and services. Your role will involve automating processes for data validation, transformation, and workflow orchestration, ensuring seamless integration of ML models into production. You will work closely with data scientists, software engineers, and product teams to optimize performance and reliability of model serving and monitoring solutions. Managing data versioning, lineage tracking, and reproducibility for ML experiments will be part of your responsibilities. You will also identify opportunities to enhance scalability, streamline deployment processes, and improve infrastructure resilience. Implementing security measures to safeguard data integrity and ensure regulatory compliance will be crucial, along with diagnosing and resolving issues throughout the data and ML pipeline lifecycle. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Data Engineering, or a related field, along with 4+ years of experience in Data DevOps, MLOps, or similar roles. Proficiency in cloud platforms like Azure, AWS, or GCP is required, as well as competency in using Infrastructure as Code (IaC) tools such as Terraform, CloudFormation, or Ansible. Expertise in containerization and orchestration technologies like Docker and Kubernetes is essential, along with a background in data processing frameworks such as Apache Spark or Databricks. Skills in Python programming, including proficiency in data manipulation and ML libraries like Pandas, TensorFlow, and PyTorch, are necessary. Familiarity with CI/CD tools such as Jenkins, GitLab CI/CD, or GitHub Actions, as well as understanding version control tools like Git and MLOps platforms such as MLflow or Kubeflow, will be valuable. Knowledge of monitoring, logging, and alerting systems (e.g., Prometheus, Grafana), strong problem-solving skills, and the ability to contribute independently and within a team are also required. Excellent communication skills and attention to documentation are essential for success in this role. Nice-to-have qualifications include knowledge of DataOps practices and tools like Airflow or dbt, an understanding of data governance concepts and platforms like Collibra, and a background in Big Data technologies like Hadoop or Hive. Qualifications in cloud platforms or data engineering would be an added advantage.,