We are seeking an experienced Product Manager-Data Management to lead the development and adoption of our 3rd party data platforms, including D&B and other similar platforms. The successful candidate will be responsible for driving the integration and utilization of 3rd party data across marketing campaigns, improving data quality and accuracy, and expanding the use cases and applications for 3rd party data. About The Role In this role as a Product Manager-Data Management, you will: Develop and execute a comprehensive strategy for 3rd party data platform adoption and expansion across the organization, with a focus on driving business outcomes and improving marketing effectiveness. Collaborate with marketing teams to integrate 3rd party data into their campaigns and workflows and provide training and support to ensure effective use of the data. Develop and showcase compelling use cases that demonstrate the value of 3rd party data in improving marketing effectiveness and measure the success of these use cases through metrics such as adoption rate, data quality, and marketing ROI. Develop and maintain a roadmap for 3rd party data platform adoption and expansion across the organization, with a focus on expanding use cases and applications for 3rd party data and developing new data-driven products and services. Monitor and measure the effectiveness of 3rd party data in driving business outcomes, and adjust the adoption strategy accordingly Work with cross-functional teams to ensure data quality and governance, and develop and maintain relationships with 3rd party data vendors to ensure seamless data integration and delivery. Drive the development of new data-driven products and services that leverage 3rd party data, and collaborate with stakeholders to prioritize and develop these products and services. Shift Timings: 2 PM to 11 PM (IST). Work from office for 2 days in a week (Mandatory). About You You’re a fit for the role of Product Manager - Data Management, if your background includes: 12+ years of experience in data management, product management, or a related field. Bachelor's or Master's degree in Computer Science, Data Science, Information Technology, or a related field. Experience with data management tools such as data warehousing, ETL (Extract, Transform, Load), data governance, and data quality. Understanding of the Marketing domain and data platforms such as Treasure Data, Salesforce, Eloqua, 6Sense, Alteryx, Tableau and Snowflake within a MarTech stack. Experience with machine learning and AI frameworks (e.g., TensorFlow, PyTorch). Expertise in SQL and Alteryx. Experience with data integration tools and technologies such as APIs, data pipelines, and data virtualization. Experience with data quality and validation tools and techniques such as data profiling, data cleansing, and data validation. Strong understanding of data modeling concepts, data architecture, and data governance. Excellent communication and collaboration skills. Ability to drive adoption and expansion of D&B data across the organization. Certifications in data management, data governance, or data science is nice to have. Experience with cloud-based data platforms (e.g., AWS, GCP, Azure) nice to have. Knowledge of machine learning and AI concepts, including supervised and unsupervised learning, neural networks, and deep learning nice to have. What’s in it For You? Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. About Us Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com. Show more Show less

Job Summary: We are seeking a passionate and skilled AI Engineer to design, develop, and deploy cutting-edge AI solutions across domains such as large language models (LLMs), computer vision, and autonomous agent workflows. You will collaborate with data scientists, researchers, and engineering teams to build intelligent systems that solve real-world problems using deep learning, transformer-based architectures, and multi-modal AI models. Key Responsibilities: Design and implement AI/ML models, especially transformer-based LLMs (e.g., BERT, GPT, LLaMA) and vision models (e.g., ViT, YOLO, Detectron2). Develop and deploy computer vision pipelines for object detection, segmentation, OCR, and image classification tasks. Build and orchestrate intelligent agent workflows using prompt engineering, memory systems, retrieval-augmented generation (RAG), and multi-agent coordination. Fine-tune and optimize pre-trained models on domain-specific datasets using frameworks like PyTorch or TensorFlow. Collaborate with cross-functional teams to understand problem requirements and translate them into scalable AI solutions. Implement inference pipelines and APIs to serve AI models efficiently using tools such as FastAPI, ONNX, or Triton Inference Server. Conduct model evaluation, benchmarking, A/B testing, and performance tuning. Stay updated with state-of-the-art research in deep learning, generative AI, and multi-modal learning. Ensure reproducibility, versioning, and documentation of all experiments and production models. Qualifications: Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. 35 years of hands-on experience in designing and deploying deep learning models. Strong knowledge of LLMs (e.g., GPT, BERT, T5), Vision Models (e.g., CNNs, Vision Transformers), and Computer Vision techniques. Experience building intelligent agents or using frameworks like LangChain, Haystack, AutoGPT, or similar. Proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow, Hugging Face Transformers, OpenCV, and Scikit-learn. Familiarity with MLOps concepts and deployment tools (Docker, Kubernetes, MLflow). Strong understanding of NLP, image processing, model fine-tuning, and optimization. Experience with cloud platforms (AWS, GCP, Azure) and GPU environments. Excellent problem-solving, communication, and teamwork skills. Preferred Qualifications: Experience in building multi-modal AI systems (e.g., combining vision + language models). Exposure to real-time inference systems and low-latency model deployment. Contributions to open-source AI projects or research publications. Familiarity with vector databases (e.g., FAISS, Pinecone, Weaviate) and RAG pipelines. Locations : Mumbai, Delhi / NCR, Bengaluru , Kolkata, Chennai, Hyderabad, Ahmedabad, Pune, India

Job Summary: The VP - Machine Learning will lead a team of 20-40 engineers, including both senior and junior talent, to build and scale foundational models that define the next generation of AI applications in India. This role combines deep technical expertise with strategic leadership, requiring someone who can navigate the evolving landscape of AI research while delivering production-ready solutions at scale. Key Responsibilities: 1.Strategic Leadership and Vision Develop and execute comprehensive ML/AI strategies aligned with BharatGen's mission. Define the technical roadmap for foundational model development across text, speech, and vision modalities. Set clear goals for the engineering organization and ensure alignment with broader company objectives. Collaborate with the CTO and executive team to shape product strategy and business priorities. 2.Team Management and Development Lead and mentor a diverse team of 20-40 ML engineers, data scientists, and researchers across all experience levels. Build high-performing teams through strategic hiring, talent development, and performance management. Foster a culture of innovation, technical excellence, and continuous learning within the organization. Develop career progression pathways for both senior and junior engineers, ensuring knowledge transfer and skill development. 3.Technical Excellence and Innovation Oversee the entire machine learning lifecycle from research to production deployment for foundational models. Incorporate cutting-edge research and emerging trends in AI, particularly in foundation models and multimodal AI systems. Ensure engineering excellence through robust MLOps practices, scalable infrastructure, and production-quality code. Drive innovation in model architecture, training methodologies, and deployment strategies specific to diverse language and cultural contexts. Proficiency in ML frameworks (PyTorch, TensorFlow), distributed training, and MLOps best practices. Understanding of cloud computing platforms and large-scale infrastructure management 4.Research Integration and Industry Trends Stay current with the latest developments in foundation models. Lead initiatives to incorporate multimodal AI capabilities. Evaluate and integrate emerging AI trends, including the shift toward AI-first applications and agentic solutions. Support partnerships with academic institutions and research organizations to maintain technical leadership. 5.Scaling and Operations Build and scale ML platforms and infrastructure to support foundational model development and deployment. Implement best practices for model training, evaluation, and monitoring at enterprise scale. Oversee the development of robust APIs and microservices for seamless integration of ML models into production environments. Ensure efficient resource utilization and cost optimization for large-scale model training and inference. 6.Cross-Functional Collaboration Work closely with product teams to translate business requirements into technical specifications. Collaborate with engineering teams on infrastructure, architecture, and scalability decisions Partner with business stakeholders to ensure ML solutions deliver measurable value and align with market needs. Communicate complex technical concepts to non-technical stakeholders across the organization. Minimum Qualifications and Experience: 1.Education and Experience: Advanced degree (Master's or PhD) in Computer Science, Machine Learning, Artificial Intelligence, or related field. 8+ years of hands-on experience in machine learning and AI, with significant experience in foundational models or large-scale ML systems. 5+ years of leadership experience managing teams of engineers, with a proven track record of scaling technical organizations. Experience in both research and production environments, with understanding of how to bridge academic research and applications. 2.Technical Expertise: Deep expertise in foundational model architectures, training methodologies, and deployment strategies. Strong background in natural language processing, computer vision, and speech processing technologies. Experience with multimodal AI systems and cross-modal learning approaches. Proficiency in ML frameworks (PyTorch, TensorFlow), distributed training, and MLOps best practices. Understanding of cloud computing platforms and large-scale infrastructure management 3.Leadership and Soft Skills: Exceptional leadership and team management capabilities, with experience developing both senior and junior talent. Strong strategic thinking and problem-solving abilities, with a track record of delivering complex technical projects. Excellent communication skills, capable of presenting to both technical teams and executive leadership. Experience with hiring, performance management, and organizational development in fast-growing companies. 4. Preferred Qualifications: Background in developing AI solutions for multilingual or multicultural contexts. Track record of publications in top-tier ML conferences or journals. Experience in startup or high-growth technology environments. Location of work: TIH-IoT, IIT Bombay Campus, Powai, Mumbai 400076. Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Job Title: MLOps Engineer - ML Platform Hiring Title: Flexible based on candidate experience – about Staff Engineer preferred Job Description We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure. You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Responsibilities Will Include Architect, develop, and maintain the ML platform to support training and inference of ML models. Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud. Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform. Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment. Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform. Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow. Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform. Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform. Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools. Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform. What Are We Looking For Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters. Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads. Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch). In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques. Familiarity with containerization technologies such as Docker and orchestration tools. Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD). Experience with AWS services such as EKS, EC2, VPC, IAM, S3, and EFS. Experience with AWS logging and monitoring tools. Strong problem-solving skills and the ability to troubleshoot complex technical issues. Excellent communication and collaboration skills to work effectively within a cross-functional team. We Would Love To See Experience with training and deploying models. Knowledge of ML model optimization techniques and memory management on GPUs. Familiarity with ML-specific data storage and retrieval systems. Understanding of security and compliance requirements in ML infrastructure. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3076101 Show more Show less

Optum is a global organization that delivers care, aided by technology to help millions of people live healthier lives. The work you do with our team will directly improve health outcomes by connecting people with the care, pharmacy benefits, data and resources they need to feel their best. Here, you will find a culture guided by diversity and inclusion, talented peers, comprehensive benefits and career development opportunities. Come make an impact on the communities we serve as you help us advance health equity on a global scale. Join us to start Caring. Connecting. Growing together. At Optum AI, we leverage data and resources to make a significant impact on the healthcare system. Our solutions have the potential to improve healthcare for everyone. We work on cutting-edge projects involving ML, NLP, and LLM techniques, continuously developing and improving generative AI methods for structured and unstructured healthcare data. Our team collaborates with world-class experts and top universities to develop innovative AI/ML solutions, often leading to patents and published papers. Primary Responsibilities Develop and implement AI and machine learning strategies for several healthcare domains Collaborate with cross-functional teams to identify and prioritize AI and machine learning initiatives Manage the development and deployment of AI and machine learning solutions Develop and run pipelines for data ingress and model output egress Develop and run scripts for ML model inference Design, implement, and maintain CI/CD pipelines for MLOps and DevOps functions Identify technical problems and develop software updates and fixes Develop scripts or tools to automate repetitive tasks Automate the provisioning and configuration of infrastructure resources Provide guidance on the best use of specific tools or technologies to achieve desired results Create documentation for infrastructure design and deployment procedures Utilize AI/ML frameworks and tools such as MLFlow, TensorFlow, PyTorch, Keras, Scikit-learn, etc. Lead and manage AI/ML teams and projects from ideation to delivery and evaluation Apply expertise in various AI/ML techniques, including deep learning, NLP, computer vision, recommender systems, reinforcement learning, and large language models Communicate complex AI/ML concepts and results to technical and non-technical audiences effectively Comply with the terms and conditions of the employment contract, company policies and procedures, and any and all directives (such as, but not limited to, transfer and/or re-assignment to different work locations, change in teams and/or work shifts, policies in regards to flexibility of work benefits and/or work environment, alternative work arrangements, and other decisions that may arise due to the changing business environment). The Company may adopt, vary or rescind these policies and directives in its absolute discretion and without any limitation (implied or otherwise) on its ability to do so Required Qualifications: Bachelors/master degree in computer science, engineering, mathematics, statistics, or a related discipline 12+ years of experience in Software Engineering, Data Science, or Analytics with 8+ years of experience in AI/ML engineering or related fields Experience with cloud platforms and services, such as AWS, Azure, GCP, etc. Experience in developing solutions in the NLP space and relevant projects Hands on Experience in AI and drive the development of innovative AI and machine learning solutions Demonstrated experience in leading and managing AI/ML teams and projects, from ideation to delivery and evaluation Experience with Azure development environments Knowledge of NLP literature, thrust areas, conference venues, and code repositories Familiarity with both open-source and OpenAI LLMs and RAG architecture Familiarity with UI tools like Streamlit, Flask, FAST APIs, Rest APIs, Docker containers Understanding of common NLP tasks such as text classification, entity recognition, entity extraction, and question answering Proficient in Python and one of PySpark or Scala. Familiarity with python tools for data processing Proficiency in multiple machine learning and AI techniques such as supervised, unsupervised, reinforcement learning, deep learning, and NLP Proficiency in Python, R, or other programming languages for data analysis and AI/ML development Proficiency in libraries such as Hugging Face and OpenAI API Proven ability to develop and deploy data pipelines, machine learning models, or applications on cloud platforms (Azure, Databricks, AzureML) Proven excellent communication, presentation, and interpersonal skills, with the ability to explain complex AI/ML concepts and results to technical and non-technical audiences Proven solid analytical, problem-solving, and decision-making skills, with the ability to balance innovation and pragmatism Proeven passion for learning and staying updated with the latest AI/ML trends and research

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Job Title: MLOps Engineer - ML Platform Hiring Title: Flexible based on candidate experience – about Staff Engineer preferred Job Description We are seeking a highly skilled and experienced MLOps Engineer to join our team and contribute to the development and maintenance of our ML platform both on premises and AWS Cloud. As a MLOps Engineer, you will be responsible for architecting, deploying, and optimizing the ML & Data platform that supports training of Machine Learning Models using NVIDIA DGX clusters and the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Your expertise in AWS services such as EKS, EC2, VPC, IAM, S3, and EFS will be crucial in ensuring the smooth operation and scalability of our ML infrastructure. You will work closely with cross-functional teams, including data scientists, software engineers, and infrastructure specialists, to ensure the smooth operation and scalability of our ML infrastructure. Your expertise in MLOps, DevOps, and knowledge of GPU clusters will be vital in enabling efficient training and deployment of ML models. Responsibilities Will Include Architect, develop, and maintain the ML platform to support training and inference of ML models. Design and implement scalable and reliable infrastructure solutions for NVIDIA clusters both on premises and AWS Cloud. Collaborate with data scientists and software engineers to define requirements and ensure seamless integration of ML and Data workflows into the platform. Optimize the platform’s performance and scalability, considering factors such as GPU resource utilization, data ingestion, model training, and deployment. Monitor and troubleshoot system performance, identifying and resolving issues to ensure the availability and reliability of the ML platform. Implement and maintain CI/CD pipelines for automated model training, evaluation, and deployment using technologies like ArgoCD and Argo Workflow. Implement and maintain monitoring stack using Prometheus and Grafana to ensure the health and performance of the platform. Manage AWS services including EKS, EC2, VPC, IAM, S3, and EFS to support the platform. Implement logging and monitoring solutions using AWS CloudWatch and other relevant tools. Stay updated with the latest advancements in MLOps, distributed computing, and GPU acceleration technologies, and proactively propose improvements to enhance the ML platform. What Are We Looking For Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. Proven experience as an MLOps Engineer or similar role, with a focus on large-scale ML and/or Data infrastructure and GPU clusters. Strong expertise in configuring and optimizing NVIDIA DGX clusters for deep learning workloads. Proficient in using the Kubernetes platform, including technologies like Helm, ArgoCD, Argo Workflow, Prometheus, and Grafana. Solid programming skills in languages like Python, Go and experience with relevant ML frameworks (e.g., TensorFlow, PyTorch). In-depth understanding of distributed computing, parallel computing, and GPU acceleration techniques. Familiarity with containerization technologies such as Docker and orchestration tools. Experience with CI/CD pipelines and automation tools for ML workflows (e.g., Jenkins, GitHub, ArgoCD). Experience with AWS services such as EKS, EC2, VPC, IAM, S3, and EFS. Experience with AWS logging and monitoring tools. Strong problem-solving skills and the ability to troubleshoot complex technical issues. Excellent communication and collaboration skills to work effectively within a cross-functional team. We Would Love To See Experience with training and deploying models. Knowledge of ML model optimization techniques and memory management on GPUs. Familiarity with ML-specific data storage and retrieval systems. Understanding of security and compliance requirements in ML infrastructure. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3076102 Show more Show less

job requisition idJR1027508 Overall Responsibilities: Experience with Machine Learning, Deep Learning, Computer Vision, NLP, Generative AI. Knowledge of algorithms, object-oriented and functional design principles, and best-practice patterns Solid understanding of common programming languages used in AI, such as Python, Java, C++, and R Advanced knowledge of statistical and algorithmic models as well as of fundamental mathematical concepts, such as linear algebra and probability Experience working with large data sets and writing efficient code capable of processing large data streams at speed. Skills: Machine Learning, Deep Learning, Computer Vision, NLP Strong hands-on experience in AI/ML/Data Science, including machine learning algorithms, deep learning, NLP, computer vision, etc. Knowledge of programming languages such as Python, R, SQL, etc. Experience with AI/ML/Data Science tools and frameworks such as TensorFlow, PyTorch, etc. Excellent problem-solving skills and ability to find creative solutions to complex data science problems. Strong communication and interpersonal skills to effectively collaborate with cross-functional teams and clients Experience: Minimum 8-12 years of experience in AI/ML/Data Science, with at least 8+ years in a leadership role Proven track record of successfully delivering AI/ML/Data Science projects Experience in mentoring and leading a team of AI/ML/Data Science professionals Day-to-Day Activities: Lead AI/ML/Data Science projects, ensuring successful delivery Mentor and guide junior team members Collaborate with cross-functional teams to provide subject matter expertise in AI/ML/Data Science Stay updated with latest AI/ML/Data Science trends and technologies Identify and evaluate new business opportunities in AI/ML/Data Science Qualification: Bachelor's or Master's degree in Computer Science, Data Science, AI, or related field Soft Skills: Excellent leadership and team management skills Strong interpersonal and communication skills Ability to work in a fast-paced and dynamic environment Good negotiation and stakeholder management skills Passionate about AI/ML/Data Science and staying updated with latest trends and technologies.

job requisition idJR1027361 Job Summary Synechron seeks a highly skilled AI/ML Engineer specializing in Natural Language Processing (NLP), Large Language Models (LLMs), Foundation Models (FMs), and Generative AI (GenAI). The successful candidate will design, develop, and deploy advanced AI solutions, contributing to innovative projects that transform monolithic systems into scalable microservices integrated with leading cloud platforms such as Azure, Amazon Bedrock, and Google Gemini. This role plays a critical part in advancing Synechrons capabilities in cutting-edge AI technologies, enabling impactful business insights and product innovations. Software Required Proficiency: Python (core librariesTensorFlow, PyTorch, Hugging Face transformers, etc.) Cloud platformsAzure, AWS, Google Cloud (familiarity with AI/ML services) ContainerizationDocker, Kubernetes Version controlGit Data management toolsSQL, NoSQL databases (e.g., MongoDB) Model deployment and MLOps toolsMLflow, CI/CD pipelines, monitoring tools Preferred Skills: Experience with cloud-native AI frameworks and SDKs Familiarity with AutoML tools Additional programming languages (e.g., Java, Scala) Overall Responsibilities Design, develop, and optimize NLP models, including advanced LLMs and Foundation Models, for diverse business use cases. Lead the development of large data pipelines for training, fine-tuning, and deploying models on big data platforms. Architect, implement, and maintain scalable AI solutions in line with MLOps best practices. Transition legacy monolithic AI systems into modular, microservices-based architectures for scalability and maintainability. Build end-to-end AI applications from scratch, including data ingestion, model training, deployment, and integration. Implement retrieval-augmented generation techniques for enhanced context understanding and response accuracy. Conduct thorough testing, validation, and debugging of AI/ML models and pipelines. Collaborate with cross-functional teams to embed AI capabilities into customer-facing and enterprise products. Support ongoing maintenance, monitoring, and scaling of deployed AI systems. Document system designs, workflows, and deployment procedures for compliance and knowledge sharing. Performance Outcomes: Production-ready AI solutions delivering high accuracy and efficiency. Robust data pipelines supporting training and inference at scale. Seamless integration of AI models with cloud infrastructure. Effective collaboration leading to innovative AI product deployment. Technical Skills (By Category) Programming Languages: Essential: Python (TensorFlow, PyTorch, Hugging Face, etc.) Preferred: Java, Scala Databases/Data Management: SQL (PostgreSQL, MySQL), NoSQL (MongoDB, DynamoDB) Cloud Technologies: Azure AI, AWS SageMaker, Bedrock, Google Cloud Vertex AI, Gemini Frameworks and Libraries: Transformers, Keras, scikit-learn, XGBoost, Hugging Face engines Development Tools & Methodologies: Docker, Kubernetes, Git, CI/CD pipelines (Jenkins, Azure DevOps) Security & Compliance: Knowledge of data security standards and privacy policies (GDPR, HIPAA as applicable) Experience 8 to 10 years of hands-on experience in AI/ML development, especially NLP and Generative AI. Demonstrated expertise in designing, fine-tuning, and deploying LLMs, FMs, and GenAI solutions. Proven ability to develop end-to-end AI applications within cloud environments. Experience transforming monolithic architectures into scalable microservices. Strong background with big data processing pipelines. Prior experience working with cloud-native AI tools and frameworks. Industry experience in finance, healthcare, or technology sectors is advantageous. Alternative Experience: Candidates with extensive research or academic experience in AI/ML, especially in NLP and large-scale data processing, are eligible if they have practical deployment experience. Day-to-Day Activities Develop and optimize sophisticated NLP/GenAI models fulfilling business requirements. Lead data pipeline construction for training and inference workflows. Collaborate with data engineers, architects, and product teams to ensure scalable deployment. Conduct model testing, validation, and performance tuning. Implement and monitor model deployment pipelines, troubleshoot issues, and improve system robustness. Document models, pipelines, and deployment procedures for audit and knowledge sharing. Stay updated with emerging AI/ML trends, integrating best practices into projects. Present findings, progress updates, and technical guidance to stakeholders. Qualifications Bachelors degree in Computer Science, Data Science, or related field; Masters or PhD preferred. Certifications in AI/ML, Cloud (e.g., AWS, Azure, Google Cloud), or Data Engineering are a plus. Proven professional experience with advanced NLP and Generative AI solutions. Commitment to continuous learning to keep pace with rapidly evolving AI technologies. Professional Competencies Strong analytical and problem-solving capabilities. Excellent communication skills, capable of translating complex technical concepts. Collaborative team player with experience working across global teams. Adaptability to rapidly changing project scopes and emerging AI trends. Innovation-driven mindset with a focus on delivering impactful solutions. Time management skills to prioritize and manage multiple projects effectively.

job requisition idJR1027352 Job Summary Synechron is seeking an analytical and innovative Senior Data Scientist to support and advance our data-driven initiatives. The ideal candidate will have a solid understanding of data science principles, hands-on experience with AI/ML tools and techniques, and the ability to interpret complex data sets to deliver actionable insights. This role contributes to the organizations strategic decision-making and technology innovation by applying advanced analytics and machine learning models in a collaborative environment. Software Required Skills: Python (including libraries such as pandas, scikit-learn, TensorFlow, PyTorch) proficiency in developing and deploying models R (optional, but preferred) Data management tools (SQL, NoSQL databases) Cloud platforms (preferably AWS or Azure) for data storage and ML deployment Jupyter Notebooks or similar interactive development environments Version control tools such as Git Preferred Skills: Big data technologies (Spark, Hadoop) Model deployment tools (MLflow, Docker, Kubernetes) Data visualization tools (Tableau, Power BI) Overall Responsibilities Analyze and interpret large and complex data sets to generate insights for business and technology initiatives. Assist in designing, developing, and implementing AI/ML models and algorithms to solve real-world problems. Collaborate with cross-functional teams including data engineers, software developers, and business analysts to integrate models into production systems. Stay current with emerging trends, research, and best practices in AI/ML/Data Science and apply them to ongoing projects. Document methodologies, modeling approaches, and insights clearly for technical and non-technical stakeholders. Support model validation, testing, and performance monitoring to ensure accuracy and reliability. Contribute to the development of data science workflows and standards within the organization. Performance Outcomes: Accurate and reliable data models that support strategic decision-making. Clear documentation and communication of findings and recommendations. Effective collaboration with technical teams to deploy scalable models. Continuous adoption of best practices in AI/ML and data management. Technical Skills (By Category) Programming Languages: Essential: Python (best practices in ML development), SQL Preferred: R, Java (for integration purposes) Databases/Data Management: SQL databases, NoSQL (MongoDB, Cassandra) Cloud data storage solutions (AWS S3, Azure Blob Storage) Cloud Technologies: AWS (S3, EC2, SageMaker, Lambda) Azure Machine Learning (preferred) Frameworks & Libraries: TensorFlow, PyTorch, scikit-learn, Keras, XGBoost Development Tools & Methodologies: Jupyter Notebooks, Git, CI/CD pipelines Agile and Scrum processes Security Protocols: Best practices in data security and privacy, GDPR compliance Experience 8+ years of professional experience in AI, ML, or Data Science roles. Proven hands-on experience designing and deploying ML models in real-world scenarios. Demonstrated ability to analyze complex data sets and translate findings into business insights. Previous experience working with cloud-based data science solutions is preferred. Strong portfolio showcasing data science projects, models developed, and practical impact. Alternative Pathways: Candidates with extensive research or academic experience in AI/ML can be considered, provided they demonstrate practical application of skills. Day-to-Day Activities Conduct data exploration, cleaning, feature engineering, and model development. Collaborate with data engineers to prepare data pipelines for model training. Build, validate, and refine machine learning models. Present insights, models, and recommendations to technical and business stakeholders. Support deployment of models into production environments. Monitor model performance and iterate to improve effectiveness. Participate in team meetings, project planning, and reviewing progress. Document methodologies and maintain version control of codebase. Qualifications Bachelors degree in Computer Science, Mathematics, Statistics, Data Science, or a related field; Masters or PhD highly desirable. Evidence of relevant coursework, certifications, or professional training in AI/ML. Professional certifications (e.g., AWS Certified Machine Learning Specialty, Microsoft Certified Data Scientist) are a plus. Commitment to ongoing professional development in AI/ML methodologies. Professional Competencies Strong analytical and critical thinking to solve complex problems. Effective communication skills for technical and non-technical audiences. Demonstrated ability to work collaboratively in diverse teams. Aptitude for learning new tools, techniques, and technologies rapidly. Innovation mindset with a focus on applying emerging research. Strong organizational skills to manage multiple projects and priorities.

AI / Generative AI Engineer Location: Remote ( Pan India ) Job Type: Fulltime NOTE: "Only immediate joiners or candidates with a notice period of 15 days or less will be considered" Overview: We are seeking a highly skilled and motivated AI/Generative AI Engineer to join our innovative team. The ideal candidate will have a strong background in designing, developing, and deploying artificial intelligence and machine learning models, with a specific focus on cutting-edge Generative AI technologies. This role requires hands-on experience with one or more major cloud platforms (Google Cloud Platform - GCP, Amazon Web Services - AWS) and/or modern data platforms (Databricks, Snowflake) . You will be instrumental in building and scaling AI solutions that drive business value and transform user experiences. Key Responsibilities: Design and Development: Design, build, train, and deploy scalable and robust AI/ML models, including traditional machine learning algorithms and advanced Generative AI models (e.g., Large Language Models - LLMs, diffusion models). Develop and implement algorithms for tasks such as natural language processing (NLP) , text generation, image synthesis, speech recognition, and forecasting. Work extensively with LLMs, including fine-tuning, prompt engineering, retrieval-augmented generation (RAG) , and evaluating their performance. Develop and manage data pipelines for data ingestion, preprocessing, feature engineering, and model training, ensuring data quality and integrity. Platform Expertise: Leverage cloud AI/ML services on GCP (e.g., Vertex AI, AutoML, BigQuery ML, Model Garden, Gemini) , AWS (e.g., SageMaker, Bedrock, S3 ), Databricks, and/or Snowflake to build and deploy solutions. Architect and implement AI solutions ensuring scalability, reliability, security, and cost-effectiveness on the chosen platform(s). Optimize data storage, processing, and model serving components within the cloud or data platform ecosystem. MLOps and Productionization: Implement MLOps best practices for model versioning, continuous integration/continuous deployment (CI/CD), monitoring, and lifecycle management. Deploy models into production environments and ensure their performance, scalability, and reliability. Monitor and optimize the performance of AI models in production, addressing issues related to accuracy, speed, and resource utilization. Collaboration and Innovation: Collaborate closely with data scientists, software engineers, product managers, and business stakeholders to understand requirements, define solutions, and integrate AI capabilities into applications and workflows. Stay current with the latest advancements in AI, Generative AI, machine learning, and relevant cloud/data platform technologies. Lead and participate in the ideation and prototyping of new AI applications and systems. Ensure AI solutions adhere to ethical standards, responsible AI principles, and regulatory requirements, addressing issues like data privacy, bias, and fairness. Documentation and Communication: Create and maintain comprehensive technical documentation for AI models, systems, and processes. Effectively communicate complex AI concepts and results to both technical and non-technical audiences. Required Qualifications: 8+ years of experience with software development in one or more programming languages, and with data structures/algorithms/Data Architecture. 3+ years of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision). 3+ years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field. Proven experience as an AI Engineer, Machine Learning Engineer, or a similar role. Strong programming skills in Python. Familiarity with other languages like Java, Scala, or R is a plus. Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning concepts (e.g., CNNs, RNNs, Transformer s), and statistical modeling. Hands-on experience with developing and deploying Generative AI models and techniques, including working with Large Language Models ( LLMs like GPT, BERT, LLaMA, etc .). Proficiency in using common A I/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, Keras, Hugging Face Transformers, LangChain, etc. Demonstrable experience with at least one of the following cloud/data platforms: GCP: Experience with Vertex AI, BigQuery ML, Google Cloud Storage, and other GCP AI/ML services . AWS: Experience with SageMaker, Bedrock, S3, and other AWS AI/ML services . Databricks: Experience building and scaling AI/ML solutions on the Databricks Lakehouse Platform , including MLflow. Snowflake: Experience leveraging Snowflake for data warehousing, data engineering for AI/ML workloads , and Snowpark. Experience with data engineering, including data acquisition, cleaning, transformation, and building ETL/ELT pipelines. Knowledge of MLOps tools and practices for model deployment, monitoring, and management. Familiarity with containerization technologies like Docker and orchestration tools like Kubernetes. Strong analytical and problem-solving skills. Excellent communication and collaboration abilities. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior AI Engineer (Tech Lead) Role Overview: We are seeking a highly skilled and experienced Senior AI Engineers with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Leading a team of 4-6 developers Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence Experience in leading a team of 4-6 developers Demonstrated ability to conceptualize technical solutions, apply accurate estimation techniques, and effectively engage with customer stakeholders In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior AI Engineer (Tech Lead) Role Overview: We are seeking a highly skilled and experienced Senior AI Engineers with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Leading a team of 4-6 developers Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence Experience in leading a team of 4-6 developers Demonstrated ability to conceptualize technical solutions, apply accurate estimation techniques, and effectively engage with customer stakeholders In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Overview We are looking for a talented Generative AI Developer to join our dynamic team and contribute to our projects in transforming data into actionable insights. Responsibilities Design, develop, and implement generative AI models using Python and relevant libraries. Collaborate with data scientists to analyze data and improve model performance. Develop and maintain Flask APIs to serve AI models and facilitate integration with frontend applications. Utilize SQL for data manipulation and retrieval to support AI model training and evaluation. Engage in code reviews and contribute to best practices for software development. Stay updated with the latest trends and advancements in AI and machine learning technologies. Primary Skills: Proficient in Python (including libraries such as TensorFlow, PyTorch, or similar frameworks). Strong experience with SQL for database management and data querying. Familiarity with Generative AI tools and platforms (e.g., Gemini Pro). Experience in developing RESTful APIs using Flask. Secondary Skills: Understanding of machine learning concepts and algorithms. Familiarity with cloud computing services (e.g., AWS, Google Cloud) is a plus. Knowledge of data preprocessing and feature engineering techniques. Excellent problem-solving skills and ability to work in a collaborative team environment.

Job Summary- Data Scientist with good hands-on experience of 3+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. Job Responsibilities- 1. Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib 2. Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) 3. Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence 4. Good understanding of any of the cloud platform - AWS, Azure or GCP 5. Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus 6. Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. 7. Should be able to mentor and guide mid to large sized teams under him/her Job - 1. Strong experience on Spark with Scala/Python/Java 2. Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment 3. Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering 4. Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus

Minimum 12+ years of relevant experience in building software applications in data and analytics field Enhance the go-to-market strategy by designing new and relevant solution frameworks to accelerate our clients’ journeys for impacting patient outcomes. Pitch for these opportunities and craft winning proposals to grow the Data Science Practice. Build and lead a team of data scientists and analysts, fostering a collaborative and innovative environment. Oversee the design and delivery of the models, ensuring projects are completed on time and meet business objectives. Engaging in consultative selling with clients to grow/deliver business. Develop and operationalize scalable processes to deliver on large & complex client engagements. Extensive hands-on experience with Python, R, or Julia, focusing on data science and generative AI frameworks. Expertise in working with generative models such as GPT, DALL-E, Stable Diffusion, Codex, and MidJourney for various applications. Proficiency in fine-tuning and deploying generative models using libraries like Hugging Face Transformers, Diffusers, or PyTorch Lightning. Strong understanding of generative techniques, including GANs, VAEs, diffusion models, and autoregressive models. Experience in prompt engineering, zero-shot, and few-shot learning for optimizing generative AI outputs across different use cases. Expertise in managing generative AI data pipelines, including preprocessing large-scale multimodal datasets for text, image, or code generation.

Job Summary- Data Scientist with good hands-on experience of 6+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. Job Responsibilities- Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence Good understanding of any of the cloud platform – AWS, Azure or GCP Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. Should be able to mentor and guide mid to large sized teams under him/her Job - Strong experience on Spark with Scala/Python/Java Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus

JOB OBJECTIVE Manager with good hands-on experience of 6+ years in developing state of the art and scalable Machine Learning models and their operationalization, leveraging off-the-shelf workbench production. KEY RESPONSIBILITIES Necessary Skills – 6+ years of experience of model development using Python/PySpark libraries. Development on Databricks or Dataiku DSS (Data Science Studio) environment would be a plus Strong experience on Spark with Scala/Python/Java Strong proficiency in building/training/evaluating state of the art machine learning models and its deployment Proficiency in Statistical and Probabilistic methods such as SVM, Decision-Trees, Bagging and Boosting Techniques, Clustering Proficiency in Core NLP techniques like Text Classification, Named Entity Recognition (NER), Topic Modeling, Sentiment Analysis, etc. Understanding of Generative AI / Large Language Models / Transformers would be a plus Hands on experience in Python data-science and math packages such as NumPy, Pandas, Sklearn, Seaborn, PyCaret, Matplotlib Proficiency in Python and common Machine Learning frameworks (TensorFlow, NLTK, Stanford NLP, PyTorch, Ling Pipe, Caffe, Keras, SparkML and OpenAI etc.) Experience of working in large teams and using collaboration tools like GIT, Jira and Confluence Good understanding of any of the cloud platform – AWS, Azure or GCP Understanding of Commercial Pharma landscape and Patient Data / Analytics would be a huge plus Should have an attitude of willingness to learn, accepting the challenging environment and confidence in delivering the results within timelines. Should be inclined towards self motivation and self-driven to find solutions for problems. Should be able to mentor and guide mid to large sized teams under him/her

Position Summary This Requisition is for the Employee Referral Campaign. We are seeking high-energy, driven, and innovative Data Scientists to join our Data Science Practice to develop new, specialized capabilities for Axtria, and to accelerate the company’s growth by supporting our clients’ commercial & clinical strategies. Job Responsibilities Be an Individual Contributor tothe Data Science team and solve real-world problems using cutting-edge capabilities and emerging technologies. Help clients translate the business use cases they are trying to crack into data science solutions. Provide genuine assistance to users by advising them on how to leverage Dataiku DSS to implement data science projects, from design to production. Data Source Configuration, Maintenance, Document and maintain work-instructions. Deep working onmachine learning frameworks such as TensorFlow, Caffe, Keras, SparkML Expert knowledge in Statistical and Probabilistic methods such as SVM, Decision-Trees, Clustering Expert knowledge of python data-science and math packages such as NumPy , Pandas, Sklearn Proficiency in object-oriented languages (Java and/or Kotlin),Python and common machine learning frameworks(TensorFlow, NLTK, Stanford NLP, Ling Pipe etc Education Bachelor Equivalent - Engineering Master's Equivalent - Engineering Work Experience Data Scientist 3-5 years of relevant experience in advanced statistical and mathematical models and predictive modeling using Python. Experience in the data science space prior relevant experience in Artificial intelligence and machine Learning algorithms for developing scalable models supervised and unsupervised techniques likeNLP and deep Learning Algorithms. Ability to build scalable models using Python, R-Studio, R Shiny, PySpark, Keras, and TensorFlow. Experience in delivering data science projects leveraging cloud infrastructure. Familiarity with cloud technology such as AWS / Azure and knowledge of AWS tools such as S3, EMR, EC2, Redshift, and Glue; viz tools like Tableau and Power BI. Relevant experience in Feature Engineering, Feature Selection, and Model Validation on Big Data. Knowledge of self-service analytics platforms such as Dataiku/ KNIME/ Alteryx will be an added advantage. ML Ops Engineering 3-5 years of experience with MLOps Frameworks like Kubeflow, MLFlow, Data Robot, Airflow, etc., experience with Docker and Kubernetes, OpenShift. Prior experience in end-to-end automated ecosystems including, but not limited to, building data pipelines, developing & deploying scalable models, orchestration, scheduling, automation, and ML operations. Ability to design and implement cloud solutions and ability to build MLOps pipelines on cloud solutions (AWS, MS Azure, or GCP). Programming languages like Python, Go, Ruby, or Bash, a good understanding of Linux, knowledge of frameworks such as Keras, PyTorch, TensorFlow, etc. Ability to understand tools used by data scientists and experience with software development and test automation. Good understanding of advanced AI/ML algorithms & their applications. Gen AI :Minimum of 4-6 years develop, test, and deploy Python based applications on Azure/AWS platforms.Must have basic knowledge on concepts of Generative AI / LLMs / GPT.Deep understanding of architecture and work experience on Web Technologies.Python, SQL hands-on experience.Expertise in any popular python web frameworks e.g. flask, Django etc. Familiarity with frontend technologies like HTML, JavaScript, REACT.Be an Individual Contributor in the Analytics and Development team and solve real-world problems using cutting-edge capabilities and emerging technologies based on LLM/GenAI/GPT.Can interact with client on GenAI related capabilities and use cases.

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all. Job Description: Senior AI Engineer (Tech Lead) Role Overview: We are seeking a highly skilled and experienced Senior AI Engineers with a minimum of 4 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role. Responsibilities: Your technical responsibilities: Contribute to the design and implementation of state-of-the-art AI solutions. Leading a team of 4-6 developers Assist in the development and implementation of AI models and systems, leveraging techniques such as Large Language Models (LLMs) and generative AI. Collaborate with stakeholders to identify business opportunities and define AI project goals. Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges. Utilize generative AI techniques, such as LLMs, Agentic Framework to develop innovative solutions for enterprise industry use cases. Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities. Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment. Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs. Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs. Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly. Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency. Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases. Ensure compliance with data privacy, security, and ethical considerations in AI applications. Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications. Requirements: Bachelor's or Master's degree in Computer Science, Engineering, or a related field. Minimum 4 years of experience in Python, Data Science, Machine Learning, OCR and document intelligence Experience in leading a team of 4-6 developers Demonstrated ability to conceptualize technical solutions, apply accurate estimation techniques, and effectively engage with customer stakeholders In-depth knowledge of machine learning, deep learning, and generative AI techniques. Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch. Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models. Familiarity with computer vision techniques for image recognition, object detection, or image generation. Strong knowledge of Python frameworks such as Django, Flask, or FastAPI. Experience with RESTful API design and development. Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment. Expertise in data engineering, including data curation, cleaning, and preprocessing. Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems. Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models. Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions. Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels. Understanding of data privacy, security, and ethical considerations in AI applications. Track record of driving innovation and staying updated with the latest AI research and advancements. Good to Have Skills: Understanding of agentic AI concepts and frameworks Proficiency in designing or interacting with agent-based AI architectures Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems. Utilize optimization tools and techniques, including MIP (Mixed Integer Programming). Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models. Implement CI/CD pipelines for streamlined model deployment and scaling processes. Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines. Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation. Implement monitoring and logging tools to ensure AI model performance and reliability. Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment. Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models. EY | Building a better working world EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets. Enabled by data and technology, diverse EY teams in over 150 countries provide trust through assurance and help clients grow, transform and operate. Working across assurance, consulting, law, strategy, tax and transactions, EY teams ask better questions to find new answers for the complex issues facing our world today. Show more Show less

Required Qualifications, Capabilities, and Skills: Solid understanding of backend performance optimization and debugging. Formal training or certification on software engineering concepts and proficient applied experience • Strong hands-on experience with Python Experience in developing microservices using Python with FastAPI. Commercial experience in both backend and frontend engineering Hands-on experience with AWS Cloud-based applications development, including EC2, ECS, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, EMR, and Kinesis. Strong engineering background in machine learning, deep learning, and neural networks. Experience with containerized stack using Kubernetes or ECS for development, deployment, and configuration .Experience with Single Sign-On/OIDC integration and a deep understanding of OAuth, JWT/JWE/JWS. Knowledge of AWS SageMaker and data analytics tools. Proficiency in frameworks TensorFlow, PyTorch, or similar. Preferred Qualifications, Capabilities, and Skills: Familiarity with LangChain, Langgraph, or any Agentic Frameworks is a strong plus. Python engineering experience.

We are looking for a Senior Generative AI Engineer who is passionate about cutting-edge AI innovation and has significant hands-on experience in building and deploying Generative AI models. In this role, you will be responsible for designing, fine-tuning, and optimizing large language models (LLMs), implementing innovative GenAI solutions, and contributing to the architecture of AI-driven platforms that deliver real business value. You will collaborate with cross-functional teams including data scientists, machine learning engineers, product managers, and cloud infrastructure teams to build scalable, reliable, and secure AI systems. This is a high-impact position where you will directly influence the AI roadmap and innovation strategy. Key Responsibilities : - Design, develop, and fine-tune state-of-the-art Generative AI and LLM models tailored for various business use cases. - Build, integrate, and optimize solutions using transformer-based architectures (e.g., GPT, BERT, T5, LLaMA, Mistral). - Apply techniques such as fine-tuning, prompt engineering, RLHF (Reinforcement Learning from Human Feedback), and knowledge distillation to improve model performance. - Work with vector databases (e.g., FAISS, Pinecone, Weaviate) for implementing retrieval-augmented generation (RAG) pipelines. - Develop and deploy embedding models and integrate them into LLM pipelines. - Collaborate with engineering and product teams to deploy scalable AI systems using MLOps practices and CI/CD pipelines. - Leverage LangChain, Hugging Face Transformers, OpenAI APIs, and similar frameworks/tools to accelerate development. - Optimize model performance across different environments (cloud/on-premise). - Develop end-to-end pipelines, from data preprocessing to real-time inference and monitoring. - Ensure high standards of software quality, including testing, version control, code reviews, and documentation. - Stay up to date with the latest research in Generative AI and translate breakthroughs into production-ready solutions. Required Skills & Qualifications : - Experience : 7+ years in AI/ML, data science, or software engineering; at least 3 - 4 years in Generative AI/LLMs. - Advanced Python programming skills, including familiarity with object-oriented design and software engineering best practices. - Deep expertise in PyTorch, TensorFlow, Transformers (Hugging Face), LangChain, and OpenAI or Anthropic APIs. - Experience in LLM fine-tuning, parameter-efficient tuning methods (LoRA, PEFT), RLHF, and model evaluation. - Experience with embeddings, vector stores (FAISS, Pinecone), semantic search, and RAG systems. - Hands-on experience with AWS, GCP, or Azure; knowledge of MLOps tools (SageMaker, Vertex AI, MLflow, Kubeflow) for training, deploying, and monitoring models. - Familiarity with structured/unstructured data handling and integrating AI systems with SQL/NoSQL databases. - Strong analytical thinking, problem-solving ability, and a keen interest in research and innovation.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Interested in accelerating machine learning and artificial intelligence on mobile devices for millions of usersCome join our team. We are building software platforms that enable users of Qualcomms silicon to construct optimized neural networks and machine learning algorithms. We are looking for software engineers with a machine learning or compiler background who will help us build these software platforms. In this role, you will construct and tune machine learning frameworks, build compilers and tools, and collaborate with Qualcomm hardware and software engineers to enable efficient usage of Qualcomms silicon for machine learning applications. Minimum qualifications: Bachelors degree in Engineering, Information Systems, Computer Science, or related field. Programming in C/C++ 0 to 10 years of software engineering or related work experience Preferred qualifications: Experience in machine learning frameworks such as MxNet/NNVM/TVM, Pytorch, Tensorflow, Caffe OR experience in compilers with an interest in machine learning Deep knowledge of software engineering Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Interested in accelerating machine learning and artificial intelligence on mobile devices for millions of usersCome join our team. We are building software platforms that enable users of Qualcomms silicon to construct optimized neural networks and machine learning algorithms. We are looking for software engineers with a machine learning or compiler background who will help us build these software platforms. In this role, you will construct and tune machine learning frameworks, build compilers and tools, and collaborate with Qualcomm hardware and software engineers to enable efficient usage of Qualcomms silicon for machine learning applications. Minimum qualifications: Bachelors degree in Engineering, Information Systems, Computer Science, or related field. Programming in C/C++ 2 to 4 years of software engineering or related work experience Preferred qualifications: Experience in machine learning frameworks such as MxNet/NNVM/TVM, Pytorch, Tensorflow, Caffe OR experience in compilers with an interest in machine learning Deep knowledge of software engineering Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: 2-4 years of experiences in image processing/computer vision/camera domain. Working experience with machine learning framework/packages (e.g, PyTorch, TensorFlow, Keras etc.) Strong hands on experience on developing object detection, tracking or face detection algorithms. Strong background in image and signal processing, statistics, and data analysis. Developing machine learning algorithms for advanced imaging features Strong programming skills and working experience in C/C++\ assembly programming skills, multithreading and RTOS/OS concepts\fundamentals and Python. Strong debugging skills to debug complex system level issues. Collaborate with cross-functional teams to design, implement and debug camera\multimedia features for mobiles. Good analytical and problem-solving skills. Responsibilities: Development and productize camera essential features on Qualcomm chipsets for mobile Influence camera HW architecture in Qualcomm chipsets Collaborate with systems, software, hardware teams at various stages of chipset life in design/validation/commercialization. Customer interaction to commercialize Qualcomm camera solutions. Individual contributions and working with cross functional teams on camera essential features design/planning/execution/commercialization for future Snapdragon chipsets Education requirements: RequiredBachelor's/Masters/PHd Computer Engineering and/or Electrical / Electronic Engineering Preferred Masters Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field.

Role: AI Solutions Architect Experience: 12+ years Work Locations: Ramanujan IT City, Tharamani, Chennai & MindSpace Hi-Tech City, Madhapur, Hyderabad Work Model: Hybrid Time Zone : General (Should be flexible as per the job requirements) Website Address: https://www.thryvedigital.com/ Parent Organization: https://www.highmarkhealth.org/hmk/index.shtml Role Summary: The AI Solutioning Architect leads the technical solutioning and architecture of AI-driven projects within the organization, from initial conception through to successful deployment. This role is responsible for ensuring that all AI solutions are strategically aligned with business goals, technically sound, and operationally efficient. This individual will work closely with cross-functional teams to design and implement innovative AI solutions that address complex healthcare challenges within the Healthcare IT landscape. The AI Solutioning Architect plays a critical role in defining the AI/ML strategy and ensuring its successful implementation across the organization. Essential Responsibilities: Lead the technical solutioning process for all AI-related projects, ensuring alignment with business objectives, architectural standards, and the overall AI/ML strategy. Define and maintain the architectural vision and roadmap for AI solutions, incorporating best practices, emerging technologies, and the evolving needs of the Healthcare IT domain. Design end-to-end AI solutions, including data ingestion, processing, model development, deployment, and monitoring, with a focus on scalability, reliability, and security. Work closely with business stakeholders to understand requirements and translate them into technical specifications, while also contributing to the overall strategic direction of AI initiatives. Collaborate with data scientists, engineers, and other technical experts to ensure successful project execution, providing technical guidance and mentorship throughout the development lifecycle. Develop and maintain comprehensive documentation of AI solutions, including architecture diagrams, design specifications, and implementation guidelines, to facilitate knowledge sharing and collaboration. Evaluate and recommend AI technologies, platforms, and tools to support the organization's AI initiatives, with a focus on leveraging Google Cloud Platform (GCP) services where appropriate. Provide technical guidance and mentorship to project teams, fostering a culture of innovation, excellence, and continuous improvement. Lead proof-of-concept (POC) projects to validate the feasibility and value of proposed AI solutions, ensuring that they align with the organization's strategic goals. Ensure that AI solutions are scalable, secure, and compliant with relevant regulations and standards, including HIPAA and other Healthcare IT requirements. Stay abreast of the latest trends and advancements in AI and related fields and proactively identify opportunities for innovation and competitive advantage. Work with US and Thryve leaders to provide project status, risk assessment, and strategic recommendations, ensuring that stakeholders are informed and aligned on project goals and timelines. Effectively communicate complex technical concepts to both technical and non-technical audiences, fostering collaboration and alignment across the organization. Required Skills and Qualifications: Bachelor’s or master’s degree in computer science, Artificial Intelligence, or a related field. 12+ years of experience in software development or architecture, with a significant focus on AI and machine learning. Deep understanding of AI/ML concepts and techniques, including supervised, unsupervised, and reinforcement learning, as well as experience with various AI algorithms and models. Hands-on experience with cloud computing platforms (e.g., AWS, Azure, GCP), with a strong preference for experience with Google Cloud Platform (GCP) and its AI-related services. Proven experience in designing and implementing scalable and robust AI solutions within the Healthcare IT domain. Strong programming skills in languages such as Python, Java, or Scala, as well as experience with AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Excellent communication, presentation, and interpersonal skills, with the ability to effectively communicate complex technical concepts to diverse audiences. Proven ability to lead technical discussions and influence decision-making, with a demonstrated track record of successfully driving AI initiatives within an organization. Experience in working with cross-functional teams and stakeholders, with a strong ability to collaborate and build consensus. Strong analytical and problem-solving skills, with a demonstrated ability to identify and address complex technical challenges. Knowledge of healthcare industry standards and regulations (e.g., HIPAA) is required, as well as a strong understanding of the Healthcare IT landscape. Experience with MLOps practices and tools, with a focus on automating and streamlining the AI development and deployment lifecycle. Strong leadership skills, with the ability to provide technical guidance and mentorship to project teams. Interested candidates, please share your updated resume to prithiv.muralibabu@thryvedigital.com. Referrals are welcome. Show more Show less