49 Ml Frameworks Jobs

As the Manager of Technical Engineering at Kohler Co., you will be joining the Digital Experience (DX) organization with a mission to help people live gracious, healthy, and sustainable lives. In this role, you will be a key leader focusing on integrating cutting-edge technology and design to drive a Bold ambition for customers in North America. Your responsibilities will include leading, coaching, and developing all technical and engineering resources for interconnected products and experiences. This involves overseeing global multi-disciplinary teams working on advanced technology across artificial intelligence, software engineering, and interactive content through XR development frameworks. To excel in this position, you should be an inspiring people leader, a change agent, and a technology innovator who understands modern customer expectations and knows how to translate them into reality. Your success will be measured by achieving customer outcomes, therefore, emphasizing driving results and turning strategy into tangible value through experimentation and iteration will be crucial. Key Responsibilities: - Provide proactive technical leadership across multiple complex digital products and initiatives. - Build and lead global technical teams focused on delivering quality and exceeding committed deliverables. - Scale technical teams with the right resources to ensure successful outcomes. - Lead a team of engineers working on data science, XR, and interactive & immersive content. - Identify opportunities for team training and skill advancement. - Understand the connection between business, customer outcomes, and digital technology. - Collaborate with product management, design, and engineering resources to find creative solutions. - Recruit, grow, and develop a team of passionate engineers. - Communicate effectively with various stakeholders including product managers, designers, engineers, and senior management. Qualifications/Competencies And Education/Experience: - Curiosity and creativity in mindset and practice. - Ability to foster a collaborative culture and proficiency in collaboration tools. - Track record of delivering interconnected digital products across complex channels. - Strong communication skills for varied audiences. - Self-driven with the ability to deliver on ambiguous projects. - Bachelors or masters degree in computer science, engineering, or a related field. - 12-15 years of experience in digital product engineering or software development. - Experience in leading and managing a team of digital software engineers. - Technical expertise in API strategy, microservice architecture, and modular design. - Proficiency in 3D Graphics Programming and ML Frameworks. - Knowledge of best practices for platform engineering. - Experience in agile methodologies like Scrum, Kanban, and DevSecOps. If you are a dynamic leader with a passion for technology and innovation, and you possess the necessary qualifications and experience, we invite you to join our team at Kohler Co. where your contributions will make a meaningful impact on creating exceptional customer experiences.,

As an AI & ML Instructor at ADaSci, you will be responsible for delivering comprehensive corporate training sessions to experienced professionals. Your deep expertise in artificial intelligence (AI), machine learning (ML), cloud platforms (Azure, AWS, GCP), data engineering, and MLOps will enable you to design engaging and informative training sessions that empower professionals to excel in their field. Your key responsibilities will include developing and delivering training sessions on AI, ML, and related topics, designing hands-on labs and practical exercises to enhance learning, customizing training materials to meet the specific needs of corporate clients, providing real-world examples and case studies to illustrate concepts, evaluating participants" progress, and staying updated on the latest trends in AI, ML, cloud computing, data engineering, and MLOps. To excel in this role, you should possess a graduate degree with 10+ years of experience, postgraduate degree with 5+ years of experience, or a PhD with 2+ years of experience. You should have proven experience as an instructor or trainer in AI, ML, data engineering, or related fields, deep knowledge of AI and ML algorithms, proficiency in cloud platforms, experience with MLOps, strong understanding of data engineering principles, and familiarity with system design and architecture. Preferred skills include hands-on experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn), knowledge of containerization technologies like Docker, experience with big data technologies (e.g., Hadoop, Spark), and previous experience in corporate training or educational settings. Strong communication, presentation, problem-solving skills, and the ability to adapt training content for diverse audiences are essential for success in this role.,

As a Senior AI/ML Engineer/Lead at our company located in Mohali, you will play a crucial role in leading the design, architecture, and delivery of complex AI/ML solutions. With over 8 years of experience, you will be responsible for developing and implementing machine learning models across various domains like NLP, computer vision, recommendation systems, classification, and regression. Your expertise will be utilized to integrate Large Language Models (LLMs) such as GPT, BERT, LLaMA, and other state-of-the-art transformer architectures into our enterprise-grade applications to drive innovation. Your key responsibilities will include selecting and implementing ML frameworks, tools, and cloud technologies that align with our business goals. You will lead AI/ML experimentation, PoCs, benchmarking, and model optimization initiatives while collaborating with data engineering, software development, and product teams to integrate ML capabilities seamlessly into production systems. Additionally, you will establish and enforce robust MLOps pipelines covering CI/CD for ML, model versioning, reproducibility, and monitoring to ensure reliability at scale. To excel in this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a closely related field. Your hands-on experience in the AI/ML domain, along with a proven track record of delivering production-grade ML systems, will be highly valued. Proficiency in machine learning algorithms, deep learning architectures, and advanced neural network design is essential. You should also possess expertise in LLMs, transformer-based models, prompt engineering, and embeddings, with strong programming skills in Python and familiarity with cloud platforms for scalable ML workloads. Having experience with MLOps tools and practices, such as MLflow, Kubeflow, SageMaker, or equivalent, will be beneficial. Furthermore, exposure to vector databases, real-time AI systems, edge AI, streaming data environments, and active contributions to open-source projects, research publications, or thought leadership in AI/ML will be advantageous. A certification in AI/ML would be a significant plus. If you are a self-driven individual with excellent leadership, analytical thinking, and communication skills, and if you are passionate about staying updated on AI advancements and championing their adoption in business use, we encourage you to apply for this exciting opportunity.,

You will be working as a Machine Learning Intern for a duration of 6 months with a stipend of 20k per month. The internship involves a hybrid mode of working, with 3 days in the office and 2 days working from home. Your primary responsibilities will include designing and implementing cutting-edge machine learning models for complex tabular and time series data problems. Additionally, you will be tasked with developing innovative feature engineering techniques to maximize the value extracted from datasets. Researching and applying state-of-the-art algorithms in areas like automated machine learning (AutoML) and neural architecture search will also be part of your role. Furthermore, you will optimize models for performance and scalability in resource-constrained environments, contribute to the development of the company's core ML infrastructure and pipelines, and collaborate on end-to-end ML projects from problem definition to deployment and monitoring. Your involvement in strategic discussions to identify new opportunities for ML applications within the business and conducting independent research to stay updated on the latest ML advancements for tabular and time series data will be crucial. To excel in this role, you should possess a strong theoretical understanding of machine learning concepts, statistical modeling, and optimization techniques. Proven experience in developing and deploying ML models for tabular and time series data, along with advanced programming skills in Python and expertise in ML libraries and frameworks, is essential. Proficiency in working with large-scale datasets and distributed computing environments, as well as experience with modern ML techniques such as gradient boosting, neural networks, and ensemble methods, are also required. Preferred qualifications include contributions to open-source ML projects or research publications, as well as experience with cloud-native ML development and deployment. This internship offers a unique opportunity to work on cutting-edge AI and blockchain intersection projects, contributing to the company's growth and innovation in the field of machine learning.,

As a Senior Member of Technical Staff (SMTS) Software Systems Design Engineer at AMD (Advanced Micro Devices), you will play a crucial role in developing and implementing the overall QA strategy and frameworks for testing embedded and GPU-based software products across various hardware and software configurations. Your responsibilities will include evaluating and enhancing existing QA methodologies, tools, and processes, collaborating with software developers and QA teams, analyzing and debugging complex failure scenarios, and ensuring compliance with industry standards and regulations. The ideal candidate for this role is a seasoned professional with a Bachelor's or Master's degree in computer science, Engineering, or a related field, along with at least 12 years of relevant experience. You should have proven expertise in a QA Architect or Senior Technical QA Engineer role, particularly in the embedded software and GPU domain. Your strong knowledge of software QA methodologies, tools, and processes, as well as your familiarity with embedded software processes, systems architecture, and GPU technologies will be essential for success in this position. In addition, you should possess programming skills in languages such as C, C++, and Python, familiarity with various embedded and GPU hardware platforms, and experience with AI/ML frameworks, models, and data center tools. Experience with automated testing tools, Continuous Integration and Continuous Deployment (CI/CD) pipelines, version control systems like Git, and bug tracking tools such as JIRA will also be beneficial for this role. As an SMTS Software Systems Design Engineer, you will be responsible for developing and maintaining comprehensive test plans, test suites, and test cases, providing training and mentorship to QA engineers, and staying current with the latest trends and technologies in the embedded software and GPU domain. Your strong analytical and problem-solving skills, excellent communication and collaboration abilities, and commitment to continuous improvement will be key assets in this position. Joining the AMD team will provide you with the opportunity to make a significant impact on next-generation computing experiences and contribute to solving the world's most important challenges. If you are a proactive and detail-oriented individual with a passion for innovation and a drive for excellence, we encourage you to apply for the role of SMTS Software Systems Design Engineer at AMD. Together, we advance towards a brighter future.,

As an AI/ML Developer at our company, you will play a crucial role in designing, developing, and deploying intelligent solutions using cutting-edge artificial intelligence and machine learning technologies. Collaborating with a team of experts in a dynamic environment, you will contribute to high-impact, real-world applications. Your responsibilities will include designing and developing AI/ML solutions based on project and business requirements, researching and implementing machine learning algorithms, and training and optimizing ML models on domain-specific datasets. You will also be involved in functional design, prototyping, and testing of AI/ML components, working within an agile development environment and taking ownership of deliverables. The ideal candidate for this role will have hands-on experience in deep learning techniques such as NLP, Speech, or Computer Vision, proficiency with ML frameworks like PyTorch or TensorFlow, and experience in developing and fine-tuning Large Language Models (LLMs). Strong Python programming skills, experience with RESTful APIs, and familiarity with cloud platforms such as AWS, Azure, or GCP are also required. Additionally, you should possess a solid understanding of algorithms, data structures, and object-oriented design, along with experience in data modeling, database schema design, and version control using Git. Strong analytical and problem-solving skills, as well as excellent verbal and written communication abilities for cross-functional collaboration, are essential. To qualify for this position, you should hold a Bachelors or Masters degree in Computer Science, Engineering, Mathematics, Statistics, or a related field, with a solid foundation in machine learning principles, algorithms, and statistical modeling. Join us in creating innovative AI/ML solutions that make a real impact in the industry.,

As a Senior Data Scientist / AI Engineer with 8-10 years of experience, you will be a vital part of our team working on developing an AI-enabled ERP solution. Your primary responsibilities will include designing scalable AI models, implementing ML pipelines, and exploring the latest AI technologies to drive innovation. Additionally, you will play a crucial role in managing and mentoring a team of data scientists and AI engineers to foster a collaborative and efficient work environment. Your key responsibilities will involve designing and building AI models from scratch, optimizing machine learning algorithms, and integrating them into our ERP solution. You will also be responsible for developing and maintaining an AI development and deployment pipeline using cloud and containerized solutions. Furthermore, conducting R&D activities to identify opportunities for AI-driven automation, working on sentiment analysis, NLP, and computer vision tasks, and deploying ML models while ensuring seamless integration into production systems will be part of your role. Collaboration with product teams to align AI strategies with business objectives, leading and mentoring a team of data scientists and AI engineers, and fostering a collaborative team culture are essential aspects of this role. Your expertise in Python and ML frameworks, strong understanding of ML algorithms, experience with deep learning architectures, NLP, and computer vision, along with hands-on experience in deploying AI models using Flask APIs, Docker, and Kubernetes are critical for success in this position. Preferred skills include knowledge of Java, experience with software development best practices, understanding of SDLC, version control, CI/CD pipelines, and experience with Big Data technologies. If you are passionate about working with AI-driven products and have a proven track record of solving real-world challenges, we are excited to hear from you! This is a full-time position located in Trivandrum/Kochi, with a remote option available initially. If you have a minimum of 8 years of experience in AI, Machine Learning, or Data Science roles, and have worked on AI model deployment or building AI pipelines, we encourage you to apply. Leadership and team management experience, along with the ability to guide and develop junior team members, are essential requirements for this role. Your strong problem-solving skills, ability to articulate AI concepts effectively, and experience in interacting with clients to communicate AI-driven solutions will be highly valued.,

As an experienced machine learning professional with expertise in deep learning and statistical modeling for earth observation data applications, your key responsibilities will include developing models for segmentation, object classification, crop monitoring, and disaster management. It is essential for you to have proficiency in Python, ML frameworks such as TensorFlow and PyTorch, and strong research skills. An advanced degree is required for this role. SatSure is a deep tech, decision intelligence company that focuses on agriculture, infrastructure, and climate action in the developing world. The company aims to make insights from earth observation data accessible to all. Joining SatSure means being at the forefront of building a deep tech company from India that aims to solve global problems. In this role, you will be responsible for implementing deep-learning models and frameworks for various applications in agriculture and infrastructure using earth observation data. You will design and implement performance evaluation frameworks, explore new methods for improving performance, and build model monitoring and active learning pipelines. Additionally, you will work on solving research problems related to land use and land cover (LULC), crop classification, change monitoring, and disaster management using earth observations. To qualify for this role, you should have a master's degree or PhD in Engineering, Statistics, Mathematics, or Computer Science with 5-8 years of experience in machine learning-based data product research and development. Proficiency in tools and frameworks related to computer science, probability, statistics, learning theory, and deep learning fundamentals is required. Experience with statistical modeling techniques and deep learning models like CNN, RNN, Transformers, and GANs is necessary. You should also be proficient in Python and have hands-on experience in using ML frameworks such as TensorFlow, PyTorch, PyTorch Lightning, and MxNet. Additional qualifications include the ability to design, develop, and optimize machine learning/deep learning models, knowledge of applying ML to earth observation data, and an appetite for research and implementing innovative solutions for complex problems. In addition to a challenging and rewarding work environment, SatSure offers benefits such as medical health cover for you and your family, access to mental health experts, dedicated allowances for learning and skill development, and a comprehensive leave policy. The interview process includes an introductory call, assessment, presentation, multiple interview rounds, and a culture/HR round. Join SatSure to be a part of a dynamic team that is making a positive impact on the world through innovative technology and deep learning solutions.,

You are an experienced AI Application Architect responsible for leading the design and integration of AI/ML capabilities into enterprise applications. Your main objective is to architect intelligent, scalable, and reliable AI solutions that are in line with both business goals and technical strategies. You will work closely with data scientists, ML engineers, and application developers to ensure seamless end-to-end solutions. Additionally, you will be required to select and implement appropriate AI frameworks, APIs, LLMs, and infrastructure tools, as well as drive architecture decisions related to GenAI, NLP, CV, predictive analytics, and agentic AI systems. You will also establish MLOps pipelines for training, testing, and deploying models at scale while ensuring compliance with AI ethics, privacy laws, and data governance policies. Furthermore, you will evaluate emerging technologies, tools, and platforms for enterprise use and act as a technical advisor to leadership on AI opportunities and risks. In terms of required skills, you should have a strong background in AI/ML architecture and solution design, along with hands-on experience in ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Proficiency in LLMs and generative AI tools like OpenAI, Azure OpenAI, LangChain, and Hugging Face is necessary. A solid programming background in Python (FastAPI, Flask) and familiarity with Java/Node.js are essential. Experience with cloud platforms (AWS/GCP/Azure) and ML toolkits like SageMaker, Azure ML, and Vertex AI is also crucial. Additionally, a good understanding of microservices, REST APIs, GraphQL, and event-driven architecture is required. Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Weaviate, as well as proficiency with CI/CD, Docker, Kubernetes, MLflow, Airflow, or similar tools, is expected. Preferred qualifications include experience with multi-agent systems, LangChain, Autogen, or Agentic AI frameworks, familiarity with data governance, model drift detection, and performance monitoring, and prior experience in industries like BFSI, Retail, Healthcare, or Manufacturing. Education-wise, a Bachelor's or master's degree in computer science, Artificial Intelligence, Data Science, or a related field is required. Certifications in AI/ML, cloud (AWS/GCP/Azure), or MLOps are considered a plus.,

As a Data Scientist specializing in Natural Language Processing (NLP), Computer Vision, Generative AI, and IoT data processing, you will play a pivotal role in the development and optimization of cutting-edge AI solutions at Comsense Technologies in Mumbai, India. Your primary responsibilities will include designing, building, and fine-tuning machine learning models for various AI applications, such as text generation, summarization, image synthesis, and IoT data analysis. Your expertise in deploying AI models on cloud (Azure) and edge environments will be crucial for ensuring scalability, security, and high availability. You will be responsible for developing robust monitoring systems to track model performance and data drift in production environments. Additionally, your role will involve collaborating with cross-functional teams, including product managers, IoT engineers, and software developers, to deliver end-to-end AI solutions. To excel in this role, you must possess strong proficiency in Python, SQL, and Azure cloud services. Experience with CI/CD pipelines, model monitoring, and performance optimization is essential. Moreover, familiarity with ML frameworks like TensorFlow, PyTorch, Hugging Face, and OpenAI APIs, as well as data pipeline tools like Airflow, will be advantageous. Your background in IoT protocols, real-time data processing frameworks, containerization using Docker, and orchestration with Kubernetes will be beneficial for integrating AI solutions into IoT ecosystems. With a solid understanding of MLOps best practices, you will be able to implement scalable AI solutions on cloud architecture effectively. If you have hands-on experience with edge deployment technologies, speech processing, translation APIs, streaming data solutions, AutoML tools, feature stores, and data versioning, it will be considered a plus. Your ability to stay updated on state-of-the-art AI technologies and conduct research for innovative solutions will be highly valued in this role. Join our dynamic AI-driven team at Comsense Technologies and contribute to pioneering AI-driven solutions that will shape the future of technology.,

We are looking for highly motivated and innovative Research Scientists to join our team in Bengaluru, with a focus on advancing multilingual, multicultural, and multimodal large language models (LLMs). Your primary responsibility will be to conduct cutting-edge research on Gemini, particularly in the multilingual, multicultural, and multimodal domain encompassing speech, vision, and text. This research has a direct path to impacting billions of users through Google products. This role provides a unique opportunity to contribute to foundational research in multilingual and multimodal LLMs, with a special emphasis on addressing unique challenges in the Asia-Pacific (APAC) region. You will collaborate with a world-class team at Google DeepMind globally. If you are passionate about shaping the future of human-computer interaction through multilingual and multimodal LLMs and are eager to make a significant impact on users in the APAC region and beyond, we encourage you to apply. Artificial Intelligence has the potential to be one of humanity's most valuable inventions. At Google DeepMind, we are a team of scientists, engineers, machine learning experts, and more, working together to advance the state of the art in artificial intelligence. We utilize our technologies for widespread public benefit and scientific discovery, collaborating with others on critical challenges while ensuring safety and ethics are our highest priorities. This position is within the Languages group at Google DeepMind India, where the focus is on all aspects of LLM development, making impactful contributions to enhance Gemini's multilingual performance. The group's work has also improved various Google products such as Gemini App, Assistant, Search, etc., including foundational contributions to Google Translate's expansion to 110 languages representing over 600 million speakers. As a Research Scientist at Google DeepMind, your key responsibilities will include: - Developing and evaluating multilingual, multicultural, and multimodal LLMs, designing, implementing, and evaluating capabilities in Gemini and other frontier models at Google. - Collaborating with a world-class team, working closely with other research scientists, engineers, and product teams across Google DeepMind to foster a collaborative and intellectually stimulating environment. - Contributing to real-world impact, seeing your work contribute to Gemini and other frontier models at Google with applications across various domains, directly influencing the future of Google products and services. - Contributing to the research community by sharing insights and participating in external academic workshops and conferences. The ideal candidate will possess a Ph.D. (or equivalent research experience) in Computer Science, Artificial Intelligence, or a related field, a strong publication record in top-tier AI conferences or journals, and a solid understanding of deep learning, natural language processing, computer vision, and/or speech processing. Experience with relevant ML frameworks such as JAX, TensorFlow, or PyTorch, along with excellent communication and collaboration skills, are essential. Additionally, experience with multilingual, multicultural, and/or multimodal learning in LLMs, pretraining, post-training techniques, prompt engineering, few-shot learning, and evaluations would be advantageous. Familiarity with large-scale model training and deployment, as well as strong programming skills in Python or similar languages, are also desired qualities in the ideal candidate.,

As a Machine Learning Specialist in Clinical Supply Chain, you will play a crucial role in leveraging your expertise in data science to enhance the efficiency of our clinical trial supply chain. Your responsibilities will include designing, developing, and implementing machine learning models to predict clinical supply needs, optimize inventory levels, and minimize wastage. By collaborating with various teams, such as clinical operations, supply chain, and IT, you will identify relevant data sources and seamlessly integrate machine learning solutions into existing workflows. Your key duties will involve analyzing extensive datasets from clinical trials, logistics systems, and external sources to identify trends and extract valuable insights. You will be tasked with creating tools and dashboards that facilitate real-time decision-making and scenario planning. It will also be your responsibility to ensure that the developed models adhere to performance standards, scalability requirements, and regulatory guidelines such as GxP and 21 CFR Part 11. Staying abreast of the latest advancements in machine learning and artificial intelligence, you will apply industry best practices to address the challenges faced within the clinical supply chain domain. To excel in this role, you should hold a Master's or PhD degree in Computer Science, Data Science, Engineering, or a related field and possess a minimum of 3 years of experience in machine learning, data science, or AI, preferably within healthcare or life sciences. Your practical knowledge of clinical supply chain processes, including demand forecasting, IRT systems, and logistics planning, will be invaluable. Proficiency in programming languages such as Python, R, SQL, and familiarity with ML frameworks like scikit-learn, TensorFlow, and PyTorch are essential. Additionally, your expertise in statistical modeling, time series forecasting, and optimization techniques will be crucial to your success. Effective communication skills and the ability to collaborate across departments in a dynamic environment are essential qualities for this role. Preferred qualifications include experience with clinical trial data (e.g., EDC, CTMS, IRT), knowledge of regulatory requirements in clinical research, and familiarity with cloud platforms such as AWS, Azure, and GCP, along with MLOps practices. Your technical skills in SQL, R, statistical modeling, Python, ML frameworks, time series forecasting, TensorFlow, and your deep understanding of clinical supply chain operations will be instrumental in driving data-driven decision-making and optimizing logistics within our clinical trial supply chain.,

Arivon is seeking an Artificial Intelligence (AI) Software Engineer with expertise in generative AI, Natural Language Processing (NLP), and LLM. The ideal candidate should have a minimum of 5 years of experience in NLP and Generative AI and LLM research. The role involves tasks such as language model evaluation, data processing for pre-training and fine-tuning, LLM alignment, reinforcement learning for language model tuning, and efficient training and inference. Additionally, the candidate should have experience in multilingual and multimodal modeling. The AI Software Engineer should have hands-on experience with Machine Learning (ML), NLP, and Deep Learning (DL) frameworks like PyTorch, Tensorflow, and SFT on LLM. Proficiency in leveraging LangChain for the development and integration of LLMs into various applications is essential. The candidate should demonstrate a strong ability to enhance AI functionalities through innovative applications of natural language processing and understanding. Experience with model quantization or computational optimizations is considered a plus. Familiarity with cloud platforms such as AWS, GCP, and Azure is advantageous, and prior experience in the Healthcare domain is a bonus. The role also involves designing methods, tools, and infrastructure to advance the state of the art in large language models. Responsibilities include deploying, monitoring, and managing ML models in production to ensure high availability and low latency. The candidate will be expected to manage and optimize ML infrastructure, including cloud services, containers, and orchestration tools. A Master's degree in computer science, computer engineering, or a related technical field is required, while a Ph.D. in AI, computer science, data science, or related fields is preferred. Proficiency in programming languages like Python is necessary for this role.,

As a Data Engineering Specialist, you will be responsible for assessing, capturing, and translating complex business issues into structured technical tasks for the data engineering team. This includes designing, building, launching, optimizing, and extending full-stack data and business intelligence solutions. Your role will involve supporting the build of big data environments, focusing on improving data pipelines and data quality, and working with stakeholders to meet business needs. You will create data access tools for the analytics and data scientist team, conduct code reviews, assist other developers, and train team members as required. Additionally, you will ensure that developed systems comply with industry standards and best practices while meeting project requirements. To excel in this role, you should possess a Bachelor's degree in computer science engineering or equivalent, or relevant experience. Certification in cloud technologies, especially Azure, would be beneficial. You should have 2-3+ years of development experience in building and maintaining ETL/ELT pipelines on various sources and operational programming tasks. Experience with Apache data projects or cloud platform equivalents and proficiency in programming languages like Python, Scala, R, Java, Golang, Kotlin, C, or C++ is required. Your work will involve collaborating closely with data scientists, machine learning engineers, and stakeholders to understand requirements and develop data-driven solutions. Troubleshooting, debugging, and resolving issues within generative AI system development, as well as documenting processes, specifications, and training procedures will be part of your responsibilities. In summary, this role requires a strong background in data engineering, proficiency in cloud technologies, experience with data projects and programming languages, and the ability to collaborate effectively with various stakeholders to deliver high-quality data solutions.,

You will be responsible for developing, training, and fine-tuning Machine Learning models for AI/ML applications. This includes designing and implementing data pipelines for data processing, model training, and inference. Additionally, you will be deploying models using MLOps and integrating them with cloud infrastructure. Collaboration with product managers and designers to conceptualize AI-driven features will also be a key part of your role. You will also be expected to research and implement various ML and AI techniques to improve performance. To excel in this role, you should have proficiency in Python and ML frameworks such as Scikit-learn, XGBoost, TensorFlow, PyTorch. Experience with SQL and ETL data pipelines, including data processing and feature engineering, will be beneficial. Familiarity with Docker and container-based deployments to create cloud-agnostic products is required. A strong understanding of AI and Machine Learning concepts such as Supervised Learning, Unsupervised Learning, Deep Learning, and Reinforcement Learning is essential. Knowledge of at least one cloud platform (AWS, Azure, GCP) and ML deployment strategies, preferably Azure, is preferred. Exposure to LLMs (e.g., OpenAI, Hugging Face, Mistral) and foundation models will be an advantage. Understanding of various Statistical models is also expected. If you have 5 to 7 years of experience in the relevant field and possess the mentioned skills and qualifications, we would like to hear from you.,

As a Data Science/Machine Learning Instructor at our organization, you will be responsible for conducting live instructions to educate working professionals on core topics related to Data Science and Machine Learning. This includes topics such as supervised and unsupervised learning, deep learning, model evaluation, and MLOps through engaging and interactive sessions. You will collaborate with content teams to develop labs, code walkthroughs, and real-world case studies using Python, scikit-learn, TensorFlow/PyTorch, and cloud-based Data Science/Machine Learning services. Your role will also involve providing support to learners by addressing technical queries, debugging code, reviewing notebooks, and offering constructive feedback on assignments and projects. Additionally, you will mentor learners on capstone projects such as image/video models, NLP pipelines, recommendation systems, and deployment pipelines. Continuous improvement is a key aspect of your responsibilities, which includes analyzing learner performance data to enhance modules, introduce new topics like transformers and generative models, and improve assessments. To qualify for this position, you should have a minimum of 3 years of industry or academic experience in Data Science, Machine Learning, or Artificial Intelligence. A Master's degree in Data Science, Machine Learning, Artificial Intelligence, or a Computer Science specialization in AI and Data Science/Machine Learning is required. Proficiency in Python and ML frameworks such as scikit-learn, TensorFlow, or PyTorch is essential. Familiarity with MLOps tools like Docker, Kubernetes, MLflow, and cloud ML services such as AWS SageMaker, GCP AI Platform, or Azure ML is preferred. Strong presentation and mentoring skills in live and small-group settings are necessary for this role. Prior experience in teaching or educational technology would be advantageous. If you are passionate about Data Science and Machine Learning and possess the required qualifications and skills, we invite you to join our team as a Data Science/Machine Learning Instructor.,

As an Engineering Lead at Aithon Solutions, a dynamic organization specializing in operations and technology solutions for the alternative asset management sector, you will play a pivotal role in steering the development of our Generative AI products. Your primary mandate will involve overseeing the entire product lifecycle to ensure scalability, top-notch performance, and continuous innovation. Collaborating with diverse teams, you will champion engineering excellence and cultivate a culture that thrives on high performance. Your role demands a profound understanding of AI/ML, proficiency in Python coding, expertise in distributed systems, cloud architectures, and contemporary software engineering practices. Moreover, hands-on coding experience is crucial for this position, ensuring a comprehensive grasp of the technical landscape you will be navigating. Key Responsibilities: - **Technical Leadership & Strategy:** Craft and execute the technology roadmap for our Generative AI products, aligning technological advancements with overarching business objectives. - **AI/ML Product Development:** Drive the development of AI-powered products, fine-tuning models for optimal performance, scalability, and real-world applicability. - **Engineering Excellence:** Establish industry best practices in software development, DevOps, MLOps, and cloud-native architectures to foster a culture of continuous improvement. - **Team Leadership & Scaling:** Recruit, mentor, and supervise a proficient engineering team, nurturing a culture characterized by innovation and collaborative spirit. - **Cross-Functional Collaboration:** Collaborate closely with Product, Data Science, and Business teams to translate cutting-edge AI research into practical applications. - **Scalability & Performance Optimization:** Architect and enhance distributed systems to ensure the efficient deployment of AI models across cloud and edge environments. - **Security & Compliance:** Implement robust frameworks for AI ethics, data security, and compliance with industry standards and regulations. Qualifications & Skills: - Demonstrable experience of at least 12 years in software engineering, with a minimum of 3 years in leadership positions within AI-focused enterprises. - Profound expertise in Generative AI, Deep Learning, NLP, Computer Vision, and model deployment. - Hands-on familiarity with ML frameworks and leading cloud platforms such as AWS, GCP, and Azure. - Proven track record of scaling AI/ML infrastructure and optimizing models for superior performance and cost-effectiveness. - Comprehensive understanding of distributed systems, cloud-native architectures, and microservices. - Proficiency in MLOps, CI/CD, and DevOps practices. - Strong problem-solving acumen, strategic thinking, and adept stakeholder management skills. - Ability to attract, nurture, and retain top engineering talent in a competitive marketplace. Why Join Us - Lead a forward-thinking team at the forefront of Generative AI innovation. - Contribute to the development of scalable, high-impact AI products that are shaping the future of technology. - Embrace a truly entrepreneurial culture that champions imagination, innovation, and teamwork. - Collaborate with a high-caliber, collaborative team dedicated to driving excellence in the tech industry.,

We are seeking a skilled and forward-thinking Lead Software Engineer specializing in Machine Learning with over 10 years of experience to spearhead the conceptualization, development, and implementation of cutting-edge machine learning solutions. This pivotal role necessitates robust leadership qualities, profound technical acumen, and a demonstrated track record in steering teams towards resolving intricate, large-scale challenges utilizing state-of-the-art ML technologies. In this leadership capacity, you will be responsible for mentoring teams, formulating technical roadmaps, and fostering collaboration across various departments to synchronize machine learning endeavors with business objectives. Your responsibilities will include defining and orchestrating the strategy and trajectory for ML systems and applications, as well as architecting and supervising the construction of adaptable machine learning systems and infrastructure. You will drive the creation and execution of sophisticated ML models and algorithms to tackle complex business issues, collaborate with multifaceted teams to discern ML use cases and prerequisites, and provide guidance to junior and mid-level engineers on optimal practices for ML development and deployment. It will also be imperative to oversee the performance enhancement of machine learning systems in operational settings, ensure adherence to industry standards and best practices in model development, data governance, and MLOps, and spearhead research endeavors to explore emerging ML methodologies and seamlessly integrate them into the organization's solutions. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field, with a Ph.D. being an advantageous asset. Additionally, you should possess a minimum of 10 years of software engineering experience, with at least 5 years dedicated to machine learning, and exhibit proficiency in ML frameworks and libraries like TensorFlow, PyTorch, and scikit-learn. A strong grasp of designing and constructing large-scale, distributed ML systems, advanced knowledge of data engineering tools and frameworks such as Spark, Hadoop, or Kafka, hands-on experience with cloud platforms (AWS, GCP, Azure) for ML workloads, and expertise in deploying and managing ML models in production environments using MLOps tools like MLflow or Kubeflow are essential technical skills that you should bring to the table. Moreover, a deep understanding of algorithms, data structures, system design, containerization (Docker), orchestration (Kubernetes), and exceptional problem-solving capabilities are highly valued attributes for this role. Your soft skills should include robust leadership and decision-making prowess, exceptional problem-solving and analytical thinking, excellent communication aptitude to convey technical concepts to diverse audiences, and the ability to cultivate collaboration and drive innovation across teams. Preferred qualifications include a Master's degree in Computer Science, Information Technology, or a related field, familiarity with advanced techniques like generative AI, reinforcement learning, or federated learning, experience in constructing and managing real-time data processing pipelines, knowledge of data security and privacy best practices, and a track record of publications or patents in the domain of machine learning or artificial intelligence. Key Performance Indicators for this role encompass the successful delivery of scalable, high-impact ML solutions in alignment with business objectives, effective mentorship and upskilling of team members, continuous enhancement of ML system performance and reliability, and driving innovation and adoption of emerging ML techniques to sustain a competitive advantage.,

Greetings from BMW Techworks India Role: MLOPS Engineer Location: Bangalore or Chennai Experience: 6 to 12 Years What awaits you/ Job Profile: Design and Implementation: Develop and implement a robust MLOps framework and infrastructure to support the deployment and maintenance of machine learning models. Machine Learning Model Deployment: Oversee the deployment of machine learning models into production environments, ensuring they are scalable and reliable. Monitoring and Maintenance: Continuously monitor the performance of deployed models, making necessary adjustments to maintain optimal performance and stability. Automation: Implement CI/CD pipelines for automation of model deployment, monitoring, and updates to ensure pipeline stability. Collaboration: Work closely with data scientists and stakeholders to translate business requirements into technical specifications and ensure alignment on project goals. Documentation: Maintain comprehensive documentation of MLOps processes, model performance, and system architecture to facilitate knowledge sharing and compliance. What should you bring along: Educational Background: A degree in Computer Science, Data Science, Mathematics, or a related field. Experience: Proven experience in MLOps, data analysis, and software development, with a strong emphasis on designing and maintaining MLOps frameworks. Problem-Solving Mindset: Strong analytical skills and the ability to approach complex problems with innovative solutions. Team Player: Excellent communication skills and the ability to work effectively in a team-oriented environment. Must have technical skill: MLOps Framework Expertise: In-depth knowledge of robust MLOps practices, including the design and provision of MLOps frameworks and infrastructure. AWS AI/ML Services: Proficiency in using AWS AI/ML service stacks, such as AWS SageMaker and AWS Nova, for model deployment and maintenance. Programming Languages: Proficiency in PySpark for Data Engineering and ETL Machine Learning Frameworks: Familiarity with frameworks such as TensorFlow, PyTorch, or Scikit-learn. AWS Data Engineering: Strong skills in AWS ETL services, data engineering, and Cloud data ingestion. CI/CD Automation: Experience in implementing CI/CD for automation, monitoring, and ensuring pipeline stability. Communication Skills: Ability to translate business needs into technical implementations and vice versa, ensuring alignment between stakeholders and technical teams. Initiative and ownership: Ability to independently identify and address issues, take responsibility for actions and outcomes, and proactively initiate ideas, share, and contribute to the team's success Good to have skills: Understanding of statistical methods and algorithms used in machine learning. Design Skills: A strong inclination towards exploring AI/ML solution design, acting not only as a developer but also as a solution designer. Big Data Technologies: Experience with big data technologies such as Hadoop, Spark, or Kafka. Version Control and IaaC: E.g., GitHub and Terraform.

Key Skills: Machine Learning, Data Engineering, Python, TensorFlow, PyTorch, Statistical Analysis, Cloud Platforms (AWS/GCP/Azure), Data Structures, Big Data, ML Frameworks, Model Optimization, Predictive Modeling. Key Responsibilities: Develop and implement data-driven ML predictive models to advance intelligent automation and reporting. Assess, analyze, and organize large datasets to extract meaningful insights. Execute tests to validate machine learning models and algorithms. Optimize machine learning models for improved performance and accuracy. Collaborate with cross-functional teams to integrate machine learning solutions into existing systems. Monitor and maintain machine learning models to ensure ongoing accuracy and efficiency. Research and stay updated on the latest advancements in machine learning and ML techniques and applications. Document processes, methodologies, and model performance for transparency and reproducibility. Troubleshoot and resolve issues related to machine learning model deployment and operation. Mentor and provide technical guidance to junior engineers, sharing best practices and fostering a culture of continuous learning. Experience Requirement: 6-13 years of experience in machine learning, data engineering, or software development. Strong programming skills and proficiency in languages commonly used for ML and related tasks. Big Data skills and proficiency in data structures, modeling, and visualization. Proven background in statistical analysis and data analysis to support model training and evaluation. Excellent communication skills for working with stakeholders and translating technical concepts. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn); experience with production-quality code. Strong background in statistics, mathematics, and data science. Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models at scale is a plus. Education: Any Post Graduation, Any Graduation.

The company's beliefs serve as the guiding principles driving the daily operations, centered around core values of Inclusion, Innovation, Collaboration, and Wellness. These values underscore the importance of working collaboratively as a global team, prioritizing customers, self-care, interpersonal relationships, and community involvement. As a key member of the team, your role will focus on spearheading the strategic vision and advancement of cutting-edge machine learning models and algorithms to address intricate challenges. Working closely with data scientists, software engineers, and product teams, you will leverage innovative AI/ML solutions to enhance services. Your responsibilities will include constructing scalable ML pipelines, ensuring data accuracy, and deploying models in production environments to generate valuable business insights and enhance customer experiences. Key Responsibilities: - Define and execute the strategic vision for machine learning initiatives at the organizational level. - Lead the development and optimization of advanced machine learning models. - Supervise the preprocessing and analysis of extensive datasets. - Implement and uphold ML solutions in live production environments. - Collaborate with cross-functional teams to integrate ML models into products and services. - Monitor and assess the performance of deployed models, making necessary refinements. - Provide mentorship and guidance to junior engineers and data scientists. - Publish research outcomes and contribute to industry conversations. - Represent the company at conferences and external events. - Influence the company's AI/ML strategy and contribute to long-term planning. Minimum Qualifications: - A minimum of 18 years of relevant work experience along with a Bachelor's degree or equivalent. - Profound expertise in ML frameworks such as TensorFlow, PyTorch, or scikit-learn. - Extensive hands-on experience with cloud platforms like AWS, Azure, GCP, and tools for data processing and model deployment. - Recognized as an industry authority with a robust publication history. The company offers a range of benefits that support employee well-being and professional growth. To gain insight into our culture and community, visit https://about.pypl.com/who-we-are/default.aspx If you are interested in joining our Talent Community or have any queries regarding your application, please feel free to reach out. We acknowledge the challenges posed by the confidence gap and imposter syndrome, and we encourage all candidates to apply without hesitation.,

The company believes in conducting business guided by core values of Inclusion, Innovation, Collaboration, and Wellness. Working together as a global team, with customers at the center, the values push for self-care, support, and community engagement. Job Description Summary: Design, develop, and implement machine learning models and algorithms to solve complex problems. Collaborate with data scientists, software engineers, and product teams to enhance services through innovative AI/ML solutions. Build scalable ML pipelines, ensure data quality, and deploy models to drive business insights and improve customer experiences. Job Description: **Essential Responsibilities:** - Develop and optimize machine learning models for various applications. - Preprocess and analyze large datasets to extract meaningful insights. - Deploy ML solutions into production environments using appropriate tools and frameworks. - Collaborate with cross-functional teams to integrate ML models into products and services. - Monitor and evaluate the performance of deployed models. **Minimum Qualifications:** - Minimum of 5 years of relevant work experience and a Bachelor's degree or equivalent. - Experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. - Familiarity with cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. - Several years of experience in designing, implementing, and deploying machine learning models. Our Benefits: - [List of benefits] Who We Are: Learn more about our culture and community at [Company website]. Commitment to Diversity and Inclusion For general requests or consideration of your skills, join our Talent Community. The company acknowledges challenges like the confidence gap and imposter syndrome that may hinder exceptional candidates. Don't hesitate to apply.,

As an Artificial Intelligence Specialist at Gen AI, you will be responsible for driving customer conversations, understanding customer requirements, creating Gen AI solution architectures, and developing customer proposals and RFP responses. You will guide solution engineers in creating Gen AI POCs and solutions for various industry verticals. Your role will involve staying updated on the latest technology developments, industry best practices, and incorporating them into Gen AI applications. Additionally, you will design and deploy Proof of Concepts (POCs) and Points of View (POVs) across different industry verticals to showcase the potential of Generative AI applications. To qualify for this role, you should have at least 8 years of experience in software development, with a minimum of 3 years of experience in Generative AI solution development. A bachelor's degree or higher in Computer Science, Software Engineering, or related fields is required. You should be adept at critical thinking, logical reasoning, and have a strong ability to learn new industry domains quickly. Being a team player who can deliver under pressure is essential. Furthermore, you should have experience with cloud technologies such as Azure, AWS, or GCP, as well as a good understanding of NVIDIA or similar technologies. A solid appreciation of AI/ML concepts and sound design principles is necessary for this role. In terms of required skills, you should be extremely dynamic and enthusiastic about technology. Development experience with languages like C++, Java, JavaScript, HTML, C#, Python, or node.js is preferred. You should be able to adapt quickly to new challenges and evolving technology stacks. Excellent written and verbal communication skills in English are essential, along with strong analytical and critical thinking abilities. A customer-focused attitude, initiative-taking, self-driven nature, and the ability to learn quickly are also important qualities for this role. Knowledge of Python, ML Algorithms, Statistics, source code maintenance, versioning tools, Object-Oriented Programming Concepts, debugging, and analytical skills is required. Preferred skills for this position include at least 5 years of experience in ML development and MLOps. Strong programming skills in Python, knowledge of ML, Data, and API libraries, and expertise in creating end-to-end data pipelines are advantageous. Experience with ML models, ModelOps/MLOps, AutoML, AI Ethics, Trust, Explainable AI, and popular ML frameworks like SparkML, TensorFlow, scikit-learn, XGBoost, H2O, etc., is beneficial. Familiarity with working in cloud environments (AWS, Azure, GCP) or containerized environments (Mesos, Kubernetes), interest in understanding functional and industry business challenges, and knowledge of IT industry and GenAI use cases in insurance processes are preferred. Expertise in Big Data and Data Modeling is also desirable for this role.,

At PwC, as a member of the data and analytics engineering team, you will be responsible for leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights, facilitating informed decision-making, and driving business growth. As a data science and machine learning engineer at PwC, you will focus on utilizing advanced analytics and machine learning techniques to extract insights from vast datasets, enabling data-driven decision-making. Your responsibilities will include developing predictive models, conducting statistical analysis, and creating data visualizations to address complex business challenges. You will be joining PwC as an Associate with a minimum of 1.8 to 3 years of experience. PwC is dedicated to helping organizations and individuals create the value they are seeking by delivering quality Assurance, Tax, and Advisory services. Working at PwC will provide you with opportunities to apply your skills beyond the workplace, contributing to groundbreaking solutions for clients and communities. PwC Acceleration Centers in India serve as diverse, global talent hubs that focus on delivering value to clients by providing virtual client engagement support across all PwC services and capabilities worldwide. Your role will entail the following responsibilities: - Building analytics products/accelerators using various big data technologies and analytics tools as required by stakeholders, while creating robust documentation of solutions, design decisions, and operating procedures. - Working with large-scale datasets and driving the analytics path to align with project objectives, developing and executing analytical modules on PwC's big data platform. - Engaging effectively with internal and external stakeholders to understand requirements and translate them into analytical solutions. - Meeting tight deadlines, managing multiple priorities, working independently, and navigating through ambiguous requirements. - Managing the continuous improvement of data science and machine learning practices by following industry best practices. - Staying updated on new AI research and experimenting with code. - Working in sprint cycles to develop proof-of-concepts and prototype models for demonstration to data scientists, internal stakeholders, and clients. - Understanding and implementing ETL pipelines, data ingestion, and transformation to populate data models. - Communicating clearly, asking relevant questions, and driving conversations. - Bringing new perspectives to different analytical solutions. The key skills required for this role include: - Strong Analytical Thinking skills with the ability to creatively solve business problems. - Hands-on skills in Python. - Excellent communication skills. - Self-driven and results-oriented. - Knowledge of using LLMs, Prompt Engineering for efficient work. Desired skills for the role include experience in Pyspark, ML frameworks, and PowerBI.,

Position: Senior AI/ML Engineer (68Years) – GeoAI & Conversational Systems Location:Hyderabad Team: GeoAI & Intelligent Assistants About the Role We’re seeking a seasoned AI/ML expert with 6–8years of handson experience—particularly in geospatial intelligence (GeoAI) and conversational AI—to own the endtoend design, development, and deployment of advanced machinelearning solutions, including chatbots and “copilot” assistants. You will collaborate with GIS engineers, data scientists, and product teams to build systems that understand spatial data, power decisionsupport interfaces, and engage users via natural language. Key Responsibilities GeoAI Model Development: Architect and train spatialanalysis models (e.g., landuse classification, object detection in satellite/drone imagery, changedetection pipelines) Integrate geospatial features into ML workflows (e.g., spatial joins, coordinatebased embeddings, topological data structures) Conversational AI & Copilot Systems: Design, finetune, and deploy large language models (LLMs) for domainspecific chatbots and copilots Implement NLU/NLG pipelines (intent/entity extraction, dialogue management, context handling) Build guidance interfaces (“copilots”) that assist users—e.g., query GIS datasets, autogenerate map legends, suggest spatial analysis steps Productionization & MLOps: Containerize ML services (Docker/Kubernetes), set up CI/CD for model training and serving Monitor model performance in production, implement A/B testing and continuous learning loops Data Engineering & Integration: Build and maintain ETL pipelines for largescale spatial and tabular datasets Optimize geospatial databases (PostGIS, GeoMesa) and timeseries stores for ML feature retrieval Collaboration & Leadership: Mentor junior ML engineers and data scientists on best practices in GeoAI and NLP Partner with product managers to translate requirements into technical specifications and roadmaps Conduct code reviews, design reviews, and knowledgesharing sessions Required Qualifications Experience: 6–8years in applied AI/ML roles, with at least 2years focused on geospatial machine learning and 2years on NLP/Conversational AI Technical Skills: Proficient in Python and ML frameworks (TensorFlow, PyTorch, ScikitLearn) GeoAI libraries: Rasterio, GDAL, GeoPandas, PyProj, or similar NLP/LLM toolkits: Hugging Face Transformers, Rasa, Dialogflow, or equivalents Experience finetuning and deploying LLMs (GPTseries, LLaMA, etc.) and integrating with vector databases (Pinecone, Qdrant) Strong data engineering skills: SQL, PostGIS, Apache Spark or Dask for largescale processing DevOps & MLOps: Containerization (Docker), orchestration (Kubernetes), and CI/CD tooling (Jenkins, GitHub Actions) Monitoring/logging (Prometheus, ELK/EFK stacks) and A/B testing frameworks Problemsolving & Ownership: Demonstrated ability to own features endtoend, from design through production Strong analytical mindset, with experience troubleshooting model drift, performance degradation, and bias Communication & Leadership: Excellent verbal and written communication in English Proven mentorship of junior engineers and ability to lead crossfunctional technical discussions Preferred (NicetoHave) Experience with realtime spatial analytics (e.g., streaming telemetry from IoT devices, geofencing alerts) Familiarity with cloudnative geospatial platforms (AWSGround Station, Google Earth Engine, Azure Maps) Background in userexperience design for chatbots or voice assistants (e.g., conversational UX best practices) Publications or opensource contributions in GeoAI or NLP