25 Mlops Practices Jobs

The Data Science & Analysis team in India is looking for a skilled professional to join our dynamic team. As a member of our team, you will be responsible for designing, training, and fine-tuning advanced foundational models such as text, audio, and vision using healthcare and other relevant datasets. Your focus will be on accuracy and context relevance to ensure the efficiency of our solutions. Collaboration with cross-functional teams including Business, engineering, and IT is key in seamlessly integrating AI/ML technologies into our solution offerings. You will also play a crucial role in deploying, monitoring, and managing AI models in a production environment, ensuring high availability, scalability, and performance. Staying updated with the latest advancements in AI/ML and industry trends is essential to drive innovation within the team. Adherence to industry standards and regulatory requirements, such as HIPAA, is paramount in developing AI solutions. You will be responsible for developing and maintaining comprehensive documentation for AI models, providing technical guidance and mentorship to junior AI engineers, and collaborating with stakeholders to understand and translate business needs into technical requirements. To be successful in this role, you should hold a Bachelors or Masters degree in computer science, Artificial Intelligence, Machine Learning, or a related field. With a minimum of 10 years of industry experience, including at least 5 years of hands-on experience in AI/ML, you should have a strong proficiency in Python and familiarity with popular AI/ML frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers. Experience in deploying and managing AI models in production environments, expertise in serving and inference frameworks, and practical experience in Voice AI applications are desirable skills. Additionally, familiarity with healthcare data standards, regulatory compliance, cloud computing platforms, and containerization technologies will be beneficial in this role. If you have experience with federated learning, privacy-preserving AI techniques, synthetic data generation for healthcare model training, and knowledge of healthcare, it would be considered a plus. Your ability to evaluate and select GenAI models based on performance, cost, and compliance factors will be highly valued. Guidehouse offers a comprehensive total rewards package including competitive compensation and flexible benefits. We are an Equal Opportunity Employer and encourage individuals with diverse backgrounds to apply. If you require accommodation during the application process, please contact Guidehouse Recruiting for assistance. Join us at Guidehouse and be a part of a team that values innovation, collaboration, and diversity in a supportive workplace environment.,

Job Summary: We are seeking a highly motivated and skilled LLM Engineer with 2 to 7 years of professional experience to join our growing AI team. The ideal candidate will have a strong background in natural language processing, machine learning, and hands-on experience in developing, deploying, and optimizing solutions built upon Large Language Models. You will play a crucial role in designing, implementing, and maintaining robust and scalable LLM-powered applications, contributing to the full lifecycle of our AI products. Key Responsibilities: LLM Application Development: Design, develop, and deploy innovative applications leveraging state-of-the-art Large Language Models (e.g., GPT, Llama, Gemini, Claude, etc.). This includes working with various LLM APIs and open-source models. Prompt Engineering & Optimization: Develop and refine advanced prompt engineering techniques to maximize LLM performance, accuracy, and desired output for specific use cases. Fine-tuning & Adaptation: Experiment with and implement strategies for fine-tuning pre-trained LLMs on custom datasets to improve performance for domain-specific tasks. Data Preparation & Curation: Work with diverse datasets for training, fine-tuning, and evaluating LLMs, ensuring data quality, relevance, and ethical considerations. Model Evaluation & Benchmarking: Design and execute robust evaluation methodologies to assess LLM performance, identify biases, and ensure alignment with business objectives. Implement A/B testing and other experimentation frameworks. Integration & Deployment: Integrate LLM-powered solutions into existing systems and deploy them to production environments, ensuring scalability, reliability, and low latency. Experience with MLOps practices is highly desirable. Performance Optimization: Identify and implement strategies for optimizing LLM inference, resource utilization, and cost efficiency. Research & Innovation: Stay abreast of the latest advancements in LLMs, NLP, and machine learning research. Proactively explore and propose new technologies and approaches to enhance our AI capabilities. Collaboration: Work closely with cross-functional teams including data scientists, software engineers, product managers, and researchers to deliver impactful AI solutions. Documentation: Create clear and concise documentation for models, code, and deployment procedures. Required Qualifications: Bachelor&aposs or Master&aposs degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, or a related quantitative field. 2-7 years of professional experience in a role focused on Machine Learning, Natural Language Processing, or AI development. Strong proficiency in Python and relevant ML/DL frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers). Hands-on experience with Large Language Models (LLMs) , including familiarity with their architectures (e.g., Transformers) and practical application. Experience with prompt engineering techniques and strategies. Solid understanding of NLP concepts, including text pre-processing, embeddings, semantic search, and information retrieval. Familiarity with cloud platforms (AWS, GCP, Azure) and their AI/ML services. Experience with version control systems (e.g., Git). Excellent problem-solving skills and the ability to work independently and as part of a team. Strong communication and interpersonal skills to articulate complex technical concepts to both technical and non-technical audiences. Preferred Qualifications (Bonus Points for): Experience with fine-tuning LLMs on custom datasets. Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow, Docker, Kubernetes). Experience with vector databases (e.g., Pinecone, Weaviate, Milvus) for RAG applications. Knowledge of various retrieval techniques for Retrieval Augmented Generation (RAG) systems. Understanding of ethical AI principles, bias detection, and fairness in LLMs. Contributions to open-source projects or relevant publications. Experience with distributed computing frameworks. Show more Show less

You should have a Bachelor's or Master's degree in Computer Science, AI/ML, Data Science, or a related field. With over 5 years of experience in AI/ML solution design and development, you must possess proficiency in AI/ML frameworks such as TensorFlow, PyTorch, and Scikit-learn. Strong programming skills in Python, R, or Java are essential for this role. Hands-on experience with cloud platforms like AWS, Azure, and GCP is required. A solid understanding of data engineering concepts and tools such as Spark, Hadoop, and Kafka is expected. Experience with MLOps practices, including CI/CD for AI models, is a plus. Strong problem-solving, communication, and leadership skills are crucial for success in this position. Preferred qualifications include AI/ML certifications like AWS Certified Machine Learning, Google Professional ML Engineer, etc. Experience in natural language processing (NLP) or computer vision would be beneficial. Knowledge of AI governance and ethical AI practices, as well as familiarity with AI model explainability and bias detection, are also desired qualities for this role.,

The ideal candidate for this position should have at least 6+ years of experience in Machine Learning, with a primary focus on Google Vertex AI and Python. You must possess a strong understanding of MLOps practices and hands-on experience in deploying and productionizing ML models. Proficiency in Python is a must, along with experience working with Google Vertex AI. Additionally, solid knowledge of machine learning algorithms such as XGBoost, Classification models, and BigQuery ML (BQML) is required. As a member of the team, your key responsibilities will include designing, building, and maintaining ML infrastructure on Google Cloud Platform (GCP) using tools like Vertex AI, GKE, Dataflow, BigQuery, and Cloud Functions. You will be responsible for developing and automating ML pipelines for model training, validation, deployment, and monitoring using tools like Kubeflow Pipelines, TFX, or Vertex AI Pipelines. Collaboration with Data Scientists to productionize ML models and support experimentation workflows will be essential. You will also be expected to implement model monitoring and alerting for drift, performance degradation, and data quality issues, along with managing and scaling containerized ML workloads using Kubernetes (GKE) and Docker. Setting up CI/CD workflows for ML using tools like Cloud Build, Bitbucket, Jenkins, or similar will be part of your daily tasks. Ensuring proper security, versioning, and compliance across the ML lifecycle is crucial, as well as maintaining documentation, artifacts, and reusable templates for reproducibility and auditability. Having a GCP MLE Certification will be considered a plus. This is a full-time, permanent position with the possibility of remote work. The job location is Hyderabad, and the work schedule includes day and morning shifts. Application Questions: - Do you have hands-on experience in deploying and productionizing ML models - Are you proficient in Python - Do you have experience with Google Vertex AI - Do you have solid knowledge of machine learning algorithms such as XGBoost, Classification models, BigQuery ML (BQML) If you meet the qualifications and are looking for a challenging opportunity in the field of Machine Learning, we encourage you to apply for this position.,

You will be joining Salesforce, the Customer Company, known for inspiring the future of business by combining AI, data, and CRM technologies. As part of the Marketing AI/ML Algorithms and Applications team, you will play a crucial role in enhancing Salesforce's marketing initiatives by implementing cutting-edge machine learning solutions. Your work will directly impact the effectiveness of marketing efforts, contributing to Salesforce's growth and innovation in the CRM and Agentic enterprise space. In the position of Lead / Staff Machine Learning Engineer, you will be responsible for developing and deploying ML model pipelines that drive marketing performance and deliver customer value. Working closely with cross-functional teams, you will lead the design, implementation, and operations of end-to-end ML solutions at scale. Your role will involve establishing best practices, mentoring junior engineers, and ensuring the team remains at the forefront of ML innovation. Key Responsibilities: - Define and drive the technical ML strategy, emphasizing robust model architectures and MLOps practices - Lead end-to-end ML pipeline development, focusing on automated retraining workflows and model optimization - Implement infrastructure-as-code, CI/CD pipelines, and MLOps automation for model monitoring and drift detection - Own the MLOps lifecycle, including model governance, testing standards, and incident response for production ML systems - Establish engineering standards for model deployment, testing, version control, and code quality - Design and implement monitoring solutions for model performance, data quality, and system health - Collaborate with cross-functional teams to deliver scalable ML solutions with measurable impact - Provide technical leadership in ML engineering best practices and mentor junior engineers in MLOps principles Position Requirements: - 8+ years of experience in building and deploying ML model pipelines with a focus on marketing - Expertise in AWS services, particularly SageMaker and MLflow, for ML experiment tracking and lifecycle management - Proficiency in containerization, workflow orchestration, Python programming, ML frameworks, and software engineering best practices - Experience with MLOps practices, feature engineering, feature store implementations, and big data technologies - Track record of leading ML initiatives with measurable marketing impact and strong collaboration skills Join us at Salesforce to drive transformative business impact and shape the future of customer engagement through innovative AI solutions.,

As an experienced AI Architect, you will be responsible for leading the development of AI and Machine Learning infrastructure and specialized language models for HR applications. Your role will involve establishing and leading MLOps practices and driving the creation of scalable, production-ready AI/ML systems. You will collaborate with business teams to discuss the feasibility of AI/ML use cases and translate the vision of business leaders into realistic technical implementations. Your expertise will be crucial in defining the AI architecture, selecting appropriate technologies, designing and implementing robust ML infrastructure and deployment pipelines, and establishing comprehensive MLOps practices for model training, versioning, and deployment. In this role, you will lead the development of HR-specialized language models (SLMs), implement model monitoring, observability, and performance optimization frameworks, and develop fine-tuning strategies for large language models. You will create and maintain data quality assessment and validation processes, design model versioning systems and A/B testing frameworks, and define technical standards and best practices for AI development while optimizing infrastructure for cost, performance, and scalability. To be successful in this position, you should have 7+ years of experience in ML/AI engineering or related technical roles, with at least 3 years of hands-on experience in MLOps and production ML systems. Your expertise should include fine-tuning and adapting foundation models, knowledge of model serving infrastructure and orchestration, proficiency with MLOps tools such as MLflow, Kubeflow, Weights & Biases, and experience in implementing model versioning and A/B testing frameworks. Proficiency in Python and ML frameworks like PyTorch, TensorFlow, Hugging Face, as well as experience with cloud-based ML platforms such as AWS, Azure, Google Cloud, are essential. A proven track record of deploying ML models at scale, developing AI applications for enterprise software domains, and knowledge of distributed training techniques and infrastructure will be beneficial. Familiarity with retrieval-augmented generation (RAG) systems, vector databases like Pinecone, Weaviate, Milvus, and understanding of responsible AI practices and bias mitigation are also desired. A Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field is required for this position.,

The Applications Development Intermediate Programmer Analyst position is at an intermediate level and involves contributing to the establishment and implementation of new or revised application systems and programs in collaboration with the Technology team. Your main responsibility will be to participate in applications systems analysis and programming activities. You will be required to utilize your knowledge of applications development procedures, concepts, and other technical areas to identify necessary system enhancements and define them. This may involve using script tools, analyzing code, and consulting with users, clients, and technology groups to recommend programming solutions, as well as supporting customer exposure systems. Additionally, you will apply your programming language skills to design specifications and analyze applications for vulnerabilities, security issues, testing, and debugging. As an Intermediate Programmer Analyst, you will also serve as an advisor or coach to new or lower-level analysts, identify problems, analyze information, and recommend and implement solutions. You should be able to operate with a limited level of direct supervision, exercise independence of judgment, and act as a subject matter expert to senior stakeholders and team members. In this role, you will need to assess risks when making business decisions, considering the firm's reputation, and ensuring compliance with laws and regulations. You must have 3-6 years of relevant experience in the Financial Service industry, intermediate-level experience in Applications Development, clear and concise communication skills, problem-solving abilities, and the capacity to work under pressure and manage deadlines effectively. A Bachelor's degree or equivalent experience in Computer Science, Data Science, or a related field is required. Job Requirements: - Bachelor's degree in Computer Science, Data Science, or related field; Master's degree preferred - 3+ years of experience as a Data Scientist, with at least 2 years in Generative AI - Proficiency in Python, TensorFlow, PyTorch, Transformers, and LangChain - Experience in API development on cloud platforms like AWS, Azure, GCP - Deep understanding of Machine Learning concepts - Strong analytical and problem-solving skills - Excellent communication and presentation skills Preferred Qualifications: - Experience with MLOps practices and tools - Familiarity with chatbot development frameworks - Knowledge of data visualization and reporting tools - Contributions to open-source projects or publications This role requires a motivated individual with a passion for Generative AI and a proven ability to deliver impactful results.,

Choosing Capgemini means choosing a company where you will be empowered to shape your career in the way you'd like, where you'll be supported and inspired by a collaborative community of colleagues around the world, and where you'll be able to reimagine what's possible. Join us and help the world's leading organizations unlock the value of technology and build a more sustainable, more inclusive world. Drive the strategic vision for AI/ML initiatives and align them with the company's broader AI roadmap. Lead cross-functional teams including data scientists, ML engineers, and architects to deliver scalable AI solutions. Translate complex technical insights into actionable business strategies and communicate them effectively to stakeholders. Oversee the full lifecycle of AI/ML projects, leveraging LLMs and generative AI to build innovative, data-driven applications. Ensure high standards of data quality, model performance, and system reliability while staying current with emerging AI trends. Over 10 years of experience in data science with a Masters/PhD from a Tier 1 institute, specializing in AI/ML model development and deployment. Expertise in machine learning, deep learning, NLP (including LLMs like GPT, BERT, Gemini), and big data frameworks like Spark/Hadoop. Skilled in Python, R, and deep learning libraries (TensorFlow, PyTorch, Keras), with hands-on experience in cloud platforms (AWS, GCP, Azure). Strong leadership in managing data science teams and implementing MLOps practices for scalable model delivery. Excellent communication, cross-functional collaboration, and deep understanding of data privacy, security, and agile methodologies. Work on cutting-edge AI/ML solutions using deep learning, NLP, and LLMs like GPT, BERT, and Gemini across cloud platforms (AWS, GCP, Azure). Lead and mentor data science teams to deliver scalable, secure, and production-ready models using MLOps best practices. Clear career progression paths from engineering roles to architecture and consulting. Be part of mission-critical projects that ensure security, compliance, and operational efficiency for Fortune 500 clients. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs. It delivers end-to-end services and solutions leveraging strengths from strategy and design to engineering, all fueled by its market-leading capabilities in AI, generative AI, cloud, and data, combined with its deep industry expertise and partner ecosystem.,

At Allstate, great things happen when our people work together to protect families and their belongings from life's uncertainties. For over 90 years, our innovative drive has kept us a step ahead of our customers" evolving needs. From advocating for safety measures like seat belts and airbags to being a leader in pricing sophistication, telematics, and device and identity protection. This role is responsible for leading the use of data to make decisions. You will develop and execute new machine learning predictive modeling algorithms, code tools using machine learning/predictive modeling for business decisions, integrate new data to improve modeling results, and find solutions to business problems through machine learning/predictive modeling. In addition, you will manage projects of small to medium complexity. We are seeking a Data Scientist to apply machine learning and advanced analytics to solve complex business problems. The ideal candidate will possess technical expertise, business acumen, and a passion for solving high-impact problems. Your responsibilities will include developing machine learning models, integrating new data sources, and delivering solutions that enhance decision-making. You will collaborate with cross-functional teams to translate insights into action, from design to deployment. Key Responsibilities: - Design, build, and validate statistical and machine learning models for key business problems. - Perform data exploration and analysis to uncover insights and improve model performance. - Communicate findings to stakeholders, collaborate with teams to ensure solutions are adopted. - Stay updated on modeling techniques, tools, and technologies, integrating innovative approaches. - Lead data science initiatives from planning to delivery, ensuring measurable business impact. - Provide mentorship to junior team members and lead technical teams as required. Must-Have Skills: - 4 to 8 years of experience in applied data science, delivering business value through machine learning. - Proficiency in Python with experience in libraries like scikit-learn, pandas, NumPy, and TensorFlow or PyTorch. - Strong foundation in statistical analysis, regression modeling, classification techniques, and more. - Hands-on experience with building and deploying machine learning models in cloud environments. - Ability to translate complex business problems into structured data science problems. - Strong communication, stakeholder management, analytical, and problem-solving skills. - Proactive in identifying opportunities for data-driven decision-making. - Experience in Agile or Scrum-based project environments. Preferred Skills: - Experience with Large Language Models (LLMs) and transformer architectures. - Experience with production-grade ML platforms and orchestration tools for scaling models. Primary Skills: Business Case Analyses, Data Analytics, Predictive Analytics, Predictive Modeling, Waterfall Project Management. Shift Time: Shift B (India). Recruiter Info: Annapurna Jha, email: ajhat@allstate.com. About Allstate: The Allstate Corporation is a leading insurance provider in the US, with operations in multiple countries, including India. Allstate India is a strategic business services arm focusing on technology, innovation, and operational excellence. Learn more about Allstate India here.,

Tata Electronics Pvt. Ltd. is a key global player in the electronics manufacturing industry, specializing in Electronics Manufacturing Services, Semiconductor Assembly & Test, Semiconductor Foundry, and Design Services. Established in 2020 by the Tata Group, the company's primary objective is to provide integrated solutions to global customers across the electronics and semiconductor value chain. We are looking for an AI Core Developer to join our R&D team in Bangalore. This role is centered around fundamental AI research, algorithm development, and model pre-training, focusing on innovation rather than application engineering. As an AI Core Developer, you will be involved in cutting-edge AI research, creating novel algorithms, and constructing foundation models from scratch. This position is ideal for individuals with a strong background in pre-training methodologies and algorithm development who aspire to contribute to core AI advancements. Your responsibilities will include developing and implementing innovative machine learning algorithms for various AI systems, designing pre-training pipelines for large models, prototyping new AI architectures, collaborating with research scientists and engineers, and contributing to technical publications. The ideal candidate should hold a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, with 2-4 years of hands-on experience in AI/ML development. Proficiency in Python, C/C++, knowledge of deep learning frameworks such as PyTorch and TensorFlow, and experience with model pre-training are essential requirements. Strong mathematical skills, familiarity with transformer architectures and attention mechanisms, and understanding of distributed computing are also key competencies. Preferred qualifications include advanced experience in multimodal AI systems, research contributions to top-tier AI conferences, and expertise in specific AI domains like healthcare or finance. The position is based in Bangalore, India, with a hybrid work arrangement and occasional travel for conferences and collaborations.,

As an AI/ML Engineer, you will be a valuable member of our team, contributing to the development of intelligent systems that harness the power of machine learning and artificial intelligence. Your primary responsibilities will include designing, creating, and implementing machine learning models to address a variety of use cases, such as prediction, classification, NLP, and computer vision. You will collaborate closely with diverse teams to deliver innovative solutions that tackle real-world challenges effectively. Your key responsibilities will involve: - Designing and implementing machine learning models and algorithms for different applications. - Analyzing and preprocessing extensive datasets to establish resilient training pipelines. - Staying abreast of the latest advancements in AI/ML through research and integrating relevant techniques into projects. - Training, fine-tuning, and optimizing models to ensure high performance and scalability. - Deploying models into production environments using tools like Docker, Kubernetes, or cloud services (AWS, GCP, Azure). - Working alongside software engineers, data scientists, and product teams to seamlessly integrate AI/ML solutions into applications. - Monitoring model performance in production, continuously iterating for enhancements, and documenting design decisions, code, and models for transparency and reproducibility. Preferred qualifications for this role include: - Proficiency in NLP libraries (e.g., Hugging Face Transformers, spaCy) or computer vision tools (e.g., OpenCV). - Familiarity with deep learning architectures like CNNs, RNNs, GANs, or transformer models. - Knowledge of MLOps practices and tools (e.g., MLflow, Kubeflow, SageMaker). - Previous contributions to open-source AI/ML projects or publications in relevant conferences/journals. If you are passionate about AI/ML technologies and eager to work on cutting-edge solutions that make a meaningful impact, we encourage you to apply for this exciting opportunity to join our dynamic team.,

As an Enterprise Architect & AI Expert, your role will involve defining and maintaining the enterprise architecture framework, standards, and governance. You will align IT strategy with business goals to ensure architectural integrity across systems and platforms. Leading the development of roadmaps for cloud, data, application, and infrastructure architectures will be a key responsibility. It will also be crucial to evaluate and select technologies, platforms, and tools that align with enterprise goals. You will be responsible for designing and implementing AI/ML solutions to solve complex business problems. Leading AI initiatives such as NLP, computer vision, predictive analytics, and generative AI will be part of your duties. Collaborating with data scientists, engineers, and business stakeholders to deploy AI models at scale will be essential. Ensuring ethical AI practices, data governance, and compliance with regulatory standards will also be critical. In terms of leadership and collaboration, you will act as a strategic advisor to senior leadership on technology trends and innovation. Mentoring cross-functional teams, promoting architectural best practices, and facilitating enterprise-wide workshops and architecture review boards will be part of your role. To qualify for this position, you should have a Bachelors or Masters degree in Computer Science, Engineering, or a related field. You should possess 14+ years of experience in enterprise architecture, with at least 3 years in AI/ML domains. Proven experience with cloud platforms such as AWS, Azure, GCP, microservices, and API management is required. Strong knowledge of AI/ML frameworks like TensorFlow, PyTorch, Scikit-learn, and MLOps practices is essential. Familiarity with data architecture, data lakes, and real-time analytics platforms is also expected. Excellent communication, leadership, and stakeholder management skills are necessary for this role. Mandatory skills for this position include experience in designing GenAI and RAG architectures, familiarity with AWS, Vector DB - Milvus (preferred), OpenAI or Claude, LangChain, and LlamaIndex. Thank you for considering this opportunity. Siva,

You are a skilled and motivated AI Developer with over 3+ years of hands-on experience in building, deploying, and optimizing AI/ML models. Your expertise includes strong proficiency in Python, Scikit-learn, machine learning algorithms, and practical experience of Azure AI services, Azure AI foundry, Copilot Studio, and Dataverse are mandatory. You will be responsible for designing intelligent solutions using modern deep learning and neural network architectures, integrated into scalable cloud-based environments. Your key responsibilities will include utilizing Azure AI Foundry and Copilot Studio to build AI-driven solutions that can be embedded within enterprise workflows. You will design, develop, and implement AI/ML models using Python, Scikit-learn, and modern deep learning frameworks. Additionally, you will build and optimize predictive models using structured and unstructured data from data lakes and other enterprise sources. Collaborating with data engineers to process and transform data pipelines across Azure-based environments, you will develop and integrate applications with Microsoft Dataverse for intelligent business process automation. Applying best practices in data structures and algorithm design, you will ensure high performance and scalability of AI applications. Your role will involve training, testing, and deploying machine learning, deep learning, and neural network models in production environments. Furthermore, you will be responsible for ensuring model governance, performance monitoring, and continuous learning using Azure MLOps pipelines. Collaborating cross-functionally with data scientists, product teams, and cloud architects, you will drive AI innovation within the organization. As a qualified candidate, you hold a Bachelors or Masters degree in Computer Science, Data Science, AI/ML, or a related field. With 3+ years of hands-on experience in AI/ML development, you possess practical experience with Copilot Studio and Microsoft Dataverse integrations. Expertise in Microsoft Azure is essential, particularly with services such as Azure Machine Learning, Azure Data Lake, and Azure AI Foundry. Proficiency in Python and machine learning libraries like Scikit-learn, Pandas, and NumPy is required. A solid understanding of data structures, algorithms, and object-oriented programming is essential, along with experience in data lakes, data pipelines, and large-scale data processing. Your deep understanding of neural networks, deep learning frameworks (e.g., TensorFlow, PyTorch), and model tuning will be valuable in this role. Familiarity with MLOps practices and lifecycle management on cloud platforms is beneficial. Strong problem-solving abilities, communication skills, and team collaboration are important attributes for this position. Preferred qualifications include Azure AI or Data Engineering certification, experience in deploying AI-powered applications in enterprise or SaaS environments, knowledge of generative AI or large language models (LLMs), and exposure to REST APIs, CI/CD pipelines, and version control systems like Git.,

You are a skilled AI Developer with 24 years of experience, and you will be joining a dynamic team. Your main responsibility will be to design, develop, and fine-tune AI models for image and text data, focusing on Generative AI technologies such as Generative Adversarial Networks (GANs), Variational Autoencoders (VAEs), and transformer models. You will be implementing, training, and optimizing deep learning models for Natural Language Processing (NLP), Computer Vision (CV), and multimodal AI tasks. Your role will also involve managing the end-to-end lifecycle of AI projects, including data collection, pre-processing, model training, evaluation, and deployment. Collaboration with data scientists, software engineers, and product managers to integrate AI solutions into existing systems and products will be crucial. Staying updated with the latest advancements in AI research and applying innovative techniques to solve complex problems will be expected from you. Your qualifications should include a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field, along with 2 - 4 years of hands-on experience in developing AI solutions, particularly in Generative AI models. Proficiency in programming languages such as Python and experience with AI frameworks like TensorFlow, PyTorch, or Keras is necessary. A strong understanding of deep learning algorithms, especially in generative models like GANs, VAEs, and transformer architectures, is required. Experience in pre-processing and augmenting large datasets for training AI models will be advantageous. Moreover, familiarity with cloud platforms (AWS, GCP, Azure) for model training and deployment is preferred. Excellent problem-solving skills and the ability to work collaboratively in a team are essential. Experience with Natural Language Processing (NLP) techniques and frameworks, knowledge of MLOps practices and tools for continuous integration and deployment of AI models, and familiarity with ethical AI practices, including strategies for mitigating bias and ensuring responsible AI usage, will be beneficial for this role.,

You are an experienced AI/ML Architect with over 8 years of hands-on AI/ML architecture experience, looking to join our team as a key member of the COE department. With a Ph.D. or Master's degree in Computer Science, Data Science, Artificial Intelligence, or related fields, you will be responsible for leading the design and implementation of AI/ML solutions across various industry domains. Your role will involve acting as a trusted advisor to clients, understanding their business challenges, and developing scalable AI/ML strategies aligned with their vision. Your primary responsibilities will include engaging with enterprise customers and stakeholders to gather business requirements, translating challenges into effective AI/ML solutions, and designing end-to-end ML pipelines. You will collaborate with data engineers, scientists, and business SMEs to operationalize AI/ML solutions, present technical insights to diverse audiences, and lead POCs, pilots, and full-scale implementations. Staying updated on the latest trends in AI/ML, you will contribute to proposal development, technical documentation, and pre-sales engagements. To qualify for this role, you must possess a Ph.D. or Masters degree in relevant fields, along with deep knowledge of machine learning algorithms, NLP, computer vision, and deep learning frameworks. Experience with cloud AI/ML services, strong communication skills, and a proven track record of delivering AI solutions are essential. Familiarity with MLOps practices and tools is a plus. Preferred skills include experience in building GenAI or Agentic AI applications, knowledge of data governance and ethics in AI, and the ability to lead cross-functional teams while mentoring junior data scientists/engineers. Publications or contributions to AI/ML research communities are preferred but not mandatory.,

As a NLP & Generative AI Engineer at Gigaforce, you will be part of our dynamic AI/ML team based in Noida, working on cutting-edge technologies to revolutionize the insurance claims processing industry. We are a California-based InsurTech company with a strong focus on innovation and digital transformation in the Property and Casualty sector. You must have a minimum of 2 years of hands-on experience in traditional machine learning, natural language processing, and modern generative AI techniques to be considered for this role. We are looking for individuals who are passionate about deploying GenAI solutions to production, working with open-source technologies, and handling document-centric pipelines efficiently. Your main responsibilities will include building and deploying NLP and GenAI-driven products focusing on document understanding, summarization, classification, and retrieval. You will be designing and implementing models using LLMs such as GPT, T5, and BERT, along with working on scalable, cloud-based pipelines for training, serving, and monitoring models. Collaboration is key at Gigaforce, and you will work closely with cross-functional teams including data scientists, ML engineers, product managers, and developers. Additionally, you will contribute to open-source tools and frameworks in the ML ecosystem, deploying production-ready solutions using MLOps practices, and working on distributed/cloud systems with GPU-accelerated workflows. To be successful in this role, you should have a strong grasp of traditional ML algorithms, NLP fundamentals, and modern NLP & GenAI models. Proficiency in Python, experience with cloud platforms like AWS SageMaker, GCP, or Azure ML, and familiarity with MLOps tools and distributed computing are essential. Experience with document processing pipelines and understanding insurance-related documents is a plus. If you are looking for a challenging role where you can lead the design, development, and deployment of innovative AI/ML solutions in the insurance industry, then this position at Gigaforce is the perfect opportunity for you. Join us in our mission to transform the claims lifecycle into an intelligent, end-to-end digital experience.,

As an Associate Project Manager specializing in AI/ML, you will leverage your 8+ years of experience, including 3+ years in project management, to lead and oversee the successful delivery of AI/ML projects. You will play a pivotal role in managing cross-functional teams, steering complex software projects, and spearheading AI/ML initiatives from inception to deployment. Your expertise will encompass a blend of project management proficiency and technical knowledge in machine learning systems, data pipelines, and model lifecycle management. Your responsibilities will include project planning, tracking, and execution, utilizing methodologies such as Agile, Scrum, and SDLC/Waterfall. You will demonstrate your ability to juggle multiple projects and stakeholders across both business and technical domains, while also showcasing your skills in budgeting, vendor negotiation, and resource planning. Proficiency in tools like MS Project, Excel, PowerPoint, ServiceNow, SmartSheet, and Lucidchart will be essential for effective project management. Technical exposure in AI/ML is a must-have for this role, encompassing familiarity with the AI/ML project lifecycle, ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn), and data platforms (e.g., Azure ML, AWS SageMaker, Databricks). You will be well-versed in MLOps practices, model versioning, and CI/CD pipelines for ML, collaborating closely with data scientists, ML engineers, and DevOps teams to deliver innovative AI/ML solutions. Your ability to translate business challenges into AI/ML use cases and efficiently manage delivery timelines will be paramount. In addition to your technical acumen, you will exhibit strong leadership qualities, effective decision-making skills, and impeccable organizational abilities. Your excellent communication and stakeholder management aptitudes will enable you to influence and secure buy-in from executive sponsors and cross-functional teams. Building and nurturing relationships with business leaders and technical stakeholders will be crucial for the success of AI/ML projects under your purview. Your roles and responsibilities will include leading AI/ML and software development projects end-to-end, collaborating with data science and engineering teams to define project scope and deliverables, and maintaining detailed project plans aligned with business objectives. You will monitor progress, mitigate risks, ensure timely delivery of AI/ML models and software components, and facilitate alignment between business, data, and engineering stakeholders. Tracking project metrics, ROI, and model performance post-deployment, while ensuring compliance with data governance, security, and ethical AI standards, will be integral to your responsibilities. Continuous improvement in project execution and delivery frameworks, staying abreast of AI/ML trends, and contributing to strategic planning for future initiatives will be key aspects of your role as an Associate Project Manager in AI/ML.,

As the Head of Product for our client in the Technology, Information and Media industry based in Mumbai, you will be responsible for leading AI/ML and enterprise analytics initiatives. This role requires a strategic product leader with at least 8 years of experience and a strong technical background. Your main focus will be on developing AI-first solutions that revolutionize how businesses utilize data, by leveraging cutting-edge technologies such as large language models, generative AI, and real-time data intelligence. Your responsibilities will include defining and evolving the product strategy for AI/ML-powered tools, translating customer needs into product opportunities, and integrating frontier technologies into a cohesive product vision. You will lead the ideation, scoping, and launch of ML-driven features, collaborate with cross-functional teams, and drive customer-centricity through iterative feedback loops and product analytics. Additionally, you will mentor a product team, build internal alignment, and act as a thought leader both internally and externally. To excel in this role, you should have a Masters or PhD in Computer Science, Data Science, Machine Learning, or a related field, along with 8-12 years of experience in AI/ML, advanced analytics, or enterprise-grade data science platforms. You should possess a strong grasp of ML/NLP models, GenAI/LLM stacks, and experience working with scalable architectures. Furthermore, you should have 5+ years of product management experience, including 2+ years in a leadership role, with a proven track record of shipping AI-first B2B or enterprise products. Your business and communication skills should be exceptional, with the ability to tell compelling product stories, align stakeholders around a data-driven narrative, and translate technical outputs into user value and commercial impact. Experience with MLOps platforms, growth-stage startups, enterprise SaaS companies, and global data privacy frameworks would be considered a bonus. If you are passionate about innovation, execution, and impact, and have a strong background in AI/ML and product management, this is an exciting opportunity for you to lead transformative AI initiatives and make a significant difference in the world of analytics and enterprise solutions.,

Are you excited about contributing to the development of cutting-edge AI systems that are set to revolutionize cloud infrastructure operations At Oracle Cloud Infrastructure (OCI), we are dedicated to reimagining operations for the enterprise cloud, and we are currently seeking ML Engineers to spearhead this transformation. OCI stands out as a hyperscale cloud platform where operations play a crucial role in ensuring customer success. To ensure the scalability and competitiveness of OCI, there is a pressing need to automate incident detection, diagnosis, and resolution by pushing the boundaries of AI and GenAI in cloud operations. Join our team to collaborate on building intelligent AI solutions that proactively manage cloud environments, enhance operational excellence, and provide customers with a world-class experience. If you are enthusiastic about tackling complex technical challenges and influencing the evolution of autonomous cloud technology, this opportunity is perfect for you. Responsibilities will include leading the development of AI agents tailored for cloud operations, designing and implementing tools and frameworks to support AI agent development, assessing agent performance across operational scenarios, innovating meta prompting techniques, integrating advanced LLM technologies into OCI systems, collaborating across teams, engaging with customers to validate solutions, and providing technical leadership and mentorship. The ideal candidate should have a minimum of 5 years of overall experience with at least 2 years in machine learning engineering, expertise in large language models, transformers, and GenAI technologies, experience in prompt engineering, the ability to optimize AI agent performance in real-world environments, proficiency in Python and ML frameworks like PyTorch or TensorFlow, knowledge of MLOps practices, problem-solving skills, strong communication abilities, and a degree in Computer Science, Machine Learning, or a related field. Preferred qualifications include experience in building AI assistants for enterprise applications, familiarity with multi-agent systems, reinforcement learning, or autonomous decision-making frameworks, knowledge of LLM fine-tuning, RAG, or vector database integration, a background in cloud operations or infrastructure monitoring, exposure to Oracle Cloud Infrastructure or other major cloud platforms, and contributions to open-source ML projects or publications in ML, NLP, or AI agent systems. By joining our team, you will have the opportunity to work on designing AI Agents and the infrastructure supporting them, shape the future of AI-powered cloud operations at Oracle, engage with cutting-edge AI technologies to solve real-world challenges, collaborate with a talented team, and enjoy competitive compensation, benefits, and career growth opportunities.,

You will be joining our innovative EdTech team as an experienced AI/ML Content Developer. Your primary responsibility will be to create cutting-edge educational content in the field of artificial intelligence and machine learning. You will play a key role in developing comprehensive courses that cover a wide range of AI/ML domains, starting from foundational machine learning concepts to advanced generative AI and agentic AI systems. This position presents an exciting opportunity for you to influence how the next generation of AI practitioners learn and apply these transformative technologies. In this role, your tasks will include designing and developing comprehensive courses across AI/ML domains such as machine learning, natural language processing, computer vision, generative AI, and agentic AI systems. You will create diverse content formats, including hands-on labs, interactive exercises, assessments, and project-based learning modules. Additionally, you will structure learning paths that logically progress from foundational concepts to advanced AI applications. You will also develop practical coding exercises and real-world implementation scenarios using industry-standard tools and frameworks. Ensuring the quality and industry relevance of the content will be a crucial aspect of your role. You will need to ensure that all content reflects current AI/ML best practices and stays aligned with rapidly evolving industry trends. Creating practical, real-world scenarios that simulate actual AI development workflows and challenges will be part of your responsibilities. You will also collaborate with our instructional design team to optimize learning outcomes for complex technical concepts. Furthermore, you will work closely with our platform team to ensure the seamless delivery of AI/ML content and interactive experiences. Continuous iteration and improvement of existing content based on learner feedback and performance metrics will be essential. Staying updated with the latest AI research, tools, and educational methodologies, as well as integrating emerging AI technologies and frameworks into the curriculum as they become industry-relevant, will also be part of your role. For this position, we are looking for candidates with 3+ years of hands-on industry experience in machine learning, AI development, or related technical roles. Essential qualifications include domain expertise in machine learning algorithms, deep learning architectures, and AI system design. Proficiency in Python and core data science libraries, experience with machine learning frameworks like PyTorch and TensorFlow, and expertise in natural language processing techniques are also required. Additionally, strong communication skills, the ability to explain complex AI concepts clearly, and experience in creating technical AI/ML content are essential for this role. Preferred qualifications include an advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or a related field, published research in AI/ML conferences or journals, experience with reinforcement learning and multi-agent systems, familiarity with AI safety, ethics, and responsible AI development practices, and knowledge of emerging AI architectures and research trends. Background in technical training, workshops, or mentoring in AI/ML domains and an understanding of accessibility standards in educational content are also desirable.,

Are you excited about building cutting-edge AI systems that revolutionize how cloud infrastructure is run At Oracle Cloud Infrastructure (OCI), we're reimagining operations for the enterprise cloud, and we're looking for ML Engineers to drive this transformation. OCI is a hyperscale cloud platform where operations are core to customer success. For OCI to scale and remain competitive, we need to automate incident detection, diagnosis, and resolutionpushing the limits of AI and GenAI in cloud operations. Join us to build intelligent AI solutions that proactively manage cloud environments, boost operational excellence, and deliver a world-class customer experience. If you're passionate about solving deep technical challenges and shaping the next generation of autonomous cloud, this is your moment. Lead AI Agent Development: Drive the end-to-end design and development of AI agents tailored for cloud operations, ensuring scalability, reliability, and alignment with customer needs. Architect and implement tools and frameworks that accelerate AI agent development, experimentation, deployment, and monitoring. Design and execute robust methodologies to evaluate agent performance, safety, and accuracy across diverse operational scenarios. Develop advanced meta prompting techniques to dynamically adapt prompts and maximize LLM utility in varied, real-time operational contexts. Integrate cutting-edge LLM technologies into OCI systems, leveraging fine-tuning, retrieval-augmented generation (RAG), and other advanced techniques. Partner with product, UX, and engineering teams to align technical solutions with business priorities and user experience. Collaborate directly with enterprise customers to gather requirements, validate solutions, and ensure agent effectiveness in production environments. Mentor engineers, establish best practices in AI agent engineering, and contribute to the technical vision and roadmaps. Required Qualifications: - Overall 5+ with 2+ years of experience in machine learning engineering, with hands-on experience in building AI agents and production-grade ML systems. - Proven expertise in large language models (LLMs), transformers, and GenAI technologies. - Demonstrated experience in prompt engineering and developing prompting strategies for LLM-based applications. - Demonstrated ability to evaluate and optimize AI agent performance in real-world, mission-critical environments. - Solid programming skills in Python and practical experience with ML frameworks such as PyTorch or TensorFlow. - Deep understanding of MLOps practices, including model deployment, scalability, observability, and lifecycle management. - Excellent problem-solving skills with a bias for action and execution. - Ability to convince technical leaders and executives. - Strong written and verbal communication skills, including direct collaboration with enterprise customers and cross-org teams. - Bachelor's or Master's degree in Computer Science, Machine Learning, or a related technical field. Preferred Qualifications: - Experience building AI assistants or conversational agents for enterprise applications. - Experience working with multi-agent systems, reinforcement learning, or autonomous decision-making frameworks. - Familiarity with LLM fine-tuning, RAG (Retrieval-Augmented Generation), or vector database integration. - Background in cloud operations, DevOps, or infrastructure monitoring domains. - Familiarity with Oracle Cloud Infrastructure or other major cloud platforms. - Contributions to open-source ML projects and/or Publications or patents in ML, NLP, or AI agent systems. Why Join Us - Be at the forefront of designing AI Agents and the infrastructure that powers them. - Shape the future of AI-powered cloud operations at Oracle. - Work with cutting-edge AI technologies and solve impactful real-world problems. - Collaborate with a world-class team of engineers, researchers, and product leaders. - Competitive compensation, benefits, and career growth opportunities.,

You are an experienced AI/ML Content Developer who will be joining an innovative EdTech team. Your primary responsibility will involve creating cutting-edge educational content in artificial intelligence and machine learning. This includes developing comprehensive courses covering various AI/ML domains such as machine learning, natural language processing, computer vision, generative AI, and agentic AI systems. Your role will be pivotal in shaping how the next generation of AI practitioners learn and apply these transformative technologies. Your key responsibilities will include designing and developing comprehensive courses, content creation in various formats like hands-on labs, interactive exercises, assessments, and project-based learning modules. You will also be structuring learning paths logically from foundational concepts to advanced AI applications. Practical coding exercises and real-world implementation scenarios using industry-standard tools and frameworks will be a significant part of your role. Ensuring that all content reflects current AI/ML best practices and industry trends will be crucial. You will be creating practical, real-world scenarios that replicate AI development workflows and challenges. Moreover, developing hands-on projects involving model training, fine-tuning, and deployment to provide learners with portfolio-worthy experience will be essential. Collaboration with the instructional design team to optimize learning outcomes for complex technical concepts is also expected. You will work closely with the platform team to ensure the seamless delivery of AI/ML content and interactive experiences. Continuous iteration and improvement of existing content based on learner feedback and performance metrics will be part of your responsibilities. Staying current with the latest AI research, tools, and educational methodologies is necessary. Additionally, integrating emerging AI technologies and frameworks into the curriculum as they become industry-relevant is also expected. To qualify for this role, you should have at least 3+ years of hands-on industry experience in machine learning, AI development, or related technical roles. Domain expertise in machine learning algorithms, deep learning architectures, and AI system design is required. Proficiency in Python and core data science libraries, experience with machine learning frameworks like PyTorch and/or TensorFlow, and expertise in natural language processing techniques are necessary technical skills. Strong communication skills, the ability to explain complex AI concepts clearly, and experience in creating compelling narratives around AI applications and use cases are also essential. Preferred qualifications include an advanced degree (Master's/PhD) in Computer Science, Machine Learning, Data Science, or related fields, published research in AI/ML conferences or journals, experience with reinforcement learning and multi-agent systems, familiarity with AI safety, ethics, and responsible AI development practices, and knowledge of emerging AI architectures and research trends. Background in technical training, workshops, or mentoring in AI/ML domains and understanding of accessibility standards in educational content are also desirable.,

As a Machine Learning Engineer, you will be responsible for designing and implementing end-to-end ML pipelines using GCP services and ETL tools. Your role will involve deploying and maintaining predictive ML models through containerization (Docker) and orchestration (Kubernetes). It is essential to implement MLOps practices, including CI/CD pipelines using Git, to ensure seamless operations. Additionally, creating and maintaining technical architecture diagrams for GCP service implementations will be part of your routine tasks. Your expertise in Machine Learning and Deep Learning concepts will be crucial for this role. Extensive experience with GCP services, particularly AI/ML offerings, is required to excel in this position. Proficiency in MLOps practices and tools is essential, along with hands-on experience in Docker, Kubernetes, and Git. Furthermore, experience in frontend development and API integration will be beneficial for developing frontend applications that integrate with ML and AI backend services. In this role, you will also be responsible for optimizing big data processing workflows and ML model performance. Knowledge of big data processing and analytics is expected, along with the ability to create clear technical documentation and architecture diagrams to ensure effective communication within the team. Preferred qualifications for this position include Google Cloud certifications, experience with AI and GenAI models and applications, and a background in full-stack development. An understanding of microservices architecture, experience with data pipeline optimization, and proficiency in Python, HTML, and JavaScript will further strengthen your candidacy for this role.,

About the Team and Our Scope We are a forward-thinking tech organization within Swiss Re, delivering transformative AI/ML solutions that redefine how businesses operate. Our mission is to build intelligent, secure, and scalable systems that deliver real-time insights, automation, and high-impact user experiences to clients globally. You'll join a high-velocity AI/ML team working closely with product managers, architects, and engineers to create next-gen enterprise-grade solutions. Our team is built on a startup mindset - bias to action, fast iterations, and ruthless focus on value delivery. We're not only shaping the future of AI in business - we're shaping the future of talent. This role is ideal for someone passionate about advanced AI engineering today and curious about evolving into a product leadership role tomorrow. You'll get exposure to customer discovery, roadmap planning, and strategic decision-making alongside your technical contributions. Role Overview As an AI/ML Engineer, you will play a pivotal role in the research, development, and deployment of next-generation GenAI and machine learning solutions . Your scope will go beyond retrieval-augmented generation (RAG) to include areas such as prompt engineering, long-context LLM orchestration, multi-modal model integration (voice, text, image, PDF), and agent-based workflows. You will help assess trade-offs between RAG and context-native strategies, explore hybrid techniques, and build intelligent pipelines that blend structured and unstructured data. You'll work with technologies such as LLMs, vector databases, orchestration frameworks, prompt chaining libraries, and embedding models, embedding intelligence into complex, business-critical systems. This role sits at the intersection of rapid GenAI prototyping and rigorous enterprise deployment, giving you hands-on influence over both the technical stack and the emerging product direction. Key Responsibilities Build Next-Gen GenAI Pipelines : Design, implement, and optimize pipelines across RAG, prompt engineering, long-context input handling, and multi-modal processing. Prototype, Validate, Deploy : Rapidly test ideas through PoCs, validate performance against real-world business use cases, and industrialize successful patterns. Ingest, Enrich, Embed: Construct ingestion workflows including OCR, chunking, embeddings, and indexing into vector databases to unlock unstructured data. Integrate Seamlessly: Embed GenAI services into critical business workflows, balancing scalability, compliance, latency, and observability. Explore Hybrid Strategies: Combine RAG with context-native models, retrieval mechanisms, and agentic reasoning to build robust hybrid architectures. Drive Impact with Product Thinking : Collaborate with product managers and UX designers to shape user-centric solutions and understand business context. Ensure Enterprise-Grade Quality: Deliver solutions that are secure, compliant (e.g., GDPR), explainable, and resilient - especially in regulated environments. What Makes You a Fit Must-Have Technical Expertise Proven experience with GenAI techniques and LLMs , including RAG, long-context inference, prompt tuning, and multi-modal integration. Strong hands-on skills with Python , embedding models, and orchestration libraries (e.g., LangChain, Semantic Kernel, or equivalents). Comfort with MLOps practices , including version control, CI/CD pipelines, model monitoring, and reproducibility. Ability to operate independently, deliver iteratively, and challenge assumptions with data-driven insight. Understanding of vector search optimization and retrieval tuning. Exposure to multi-modal models Nice-To-Have Qualifications Experience building and operating AI systems in regulated industries (e.g., insurance, finance, healthcare). Familiarity with Azure AI ecosystem (e.g., Azure OpenAI, Azure AI Document Intelligence, Azure Cognitive Search) and deployment practices in cloud-native environments. Experience with agentic AI architectures , tools like AutoGen, or prompt chaining frameworks. Familiarity with data privacy and auditability principles in enterprise AI. Bonus: You Think Like a Product Manager While this role is technical at its core, we highly value candidates who are curious about how AI features become products . If you're excited by the idea of influencing roadmaps, shaping requirements, or owning end-to-end value delivery - we'll give you space to grow into it. This is a role where engineering and product are not silos . If you're keen to move in that direction, we'll mentor and support your evolution. Why Join Us You'll be part of a team that's pushing AI/ML into uncharted, high-value territory. We operate with urgency, autonomy, and deep collaboration. You'll prototype fast, deliver often, and see your work shape real-world outcomes - whether in underwriting, claims, or data orchestration. And if you're looking to transition from deep tech to product leadership , this role is a launchpad. Swiss Re is an equal opportunity employer . We celebrate diversity and are committed to creating an inclusive environment for all employees. Keywords: Reference Code: 134317

Role & responsibilities Please Note - This is not a walk in interview only shortlisted candidates will be called. Your key responsibilities Proven ability to design, build, and deploy end-to-end AI/ML systems in production. Expertise in data science , including statistical analysis, experimentation, and data storytelling. Experienced in working with large-scale, real-world datasets for model training and analysis. Comfortable navigating urgency, ambiguity, and fast-changing priorities . Skilled at solving complex ML problems independently , from idea to implementation. Strong leadership experience building and guiding high-performing AI teams . Hands-on with deep learning, NLP, LLMs , and classical ML techniques. Fluent in model experimentation, tuning, optimisation , and evaluation at scale. Solid software engineering background and comfort working with data and full-stack teams . Experience with cloud platforms (GCP, AWS, Azure) and production-grade ML pipelines. Bias for action willing to jump into code, data, or ops to ship impactful AI products . Your skills and experience PhD in Computer Science, Data Science, Machine Learning, AI, or a related field. Strong programming skills in Python (preferred), with experience in Java, Scala, or Go a plus. Deep expertise with ML frameworks like TensorFlow, PyTorch, Scikit-learn. Experience with large-scale datasets , distributed data processing (e.g. Spark, Beam, Airflow). Solid foundation in data science : statistical modeling, A/B testing, time series, and experimentation. Proficient in NLP, deep learning , and working with transformer-based LLMs . Experience with MLOps practices — CI/CD, model serving, monitoring, and lifecycle management. Hands-on with cloud platforms (GCP, AWS, Azure) and tools like Vertex AI, SageMaker, or Databricks. Strong grasp of API design , system integration, and delivering AI features in full-stack products. Comfortable working with SQL/NoSQL , and data warehouses like BigQuery or Snowflake. Familiar with ethical AI, model explainability , and secure, privacy-aware AI development