Job description We are seeking a skilled and experienced Data Scientist to join our dynamic team. As Data Scientist, you will play a critical role in driving high-impact data science projects. Responsibilities: Develop and implement advanced machine learning and deep learning models for Data processing, natural language processing, computer vision. Machine Learning lifecycle: data prep, training data generation, feature engineering, optimization, experimentation, reproducibility, deployment, and end-to-end workflow management Knowledge of statistical programming languages like Python, Pandas, Numpy etc. Basic knowledge of query language like SQL. Utilize expertise in statistics, ML to extract valuable insights from complex data sets. Should have knowledge working with libraries like TensorFlow, PyTorch, scikit-learn, NLTK etc. Proven experience in Generative AI. Proven track record of successfully delivering complex data science projects. Work collaboratively with cross-functional teams to identify data science opportunities and provide innovative solutions. Deploy data science models in the form of APIs on Azure Kubernetes Service (AKS) to ensure smooth integration with existing systems. Stay updated with the latest advancements in data science, AI, and related fields, and apply them to enhance our capabilities. Qualifications: Bachelor's or Master' degree 10+ years of industry experience in data science, with a strong background in data processing, deep learning, natural language processing and generation, computer vision and statistics.

Job Roles & Responsibilities Develop, maintain, and enhance automation solutions using Python. Implement Robotic Process Automation (RPA) to automate repetitive and rule-based tasks. Leverage AI-driven solutions to automate complex decision-making processes. Design and deploy Low-Code Process Automation (LCPA) solutions to create end-to-end workflow automation. Collaborate with cross-functional teams to assess automation opportunities and translate business needs into technical solutions. Develop APIs and integrate automation tools with existing enterprise applications and data sources. Ensure scalability, security, and maintainability of automation solutions. Monitor automation performance, troubleshoot issues, and optimize processes for efficiency. Stay updated on emerging technologies in automation, AI, and process optimization. Candidate Requirements Bachelors degree in Computer Science, Engineering, or a related field. 4+ years of experience in Python development, with a strong understanding of automation frameworks. Experience with RPA tools such as UiPath, Blue Prism, or Automation Anywhere. Knowledge of AI/ML technologies and their application in process automation. Experience with Low-Code/No-Code platforms such as Appian, Power Automate, or Mendix. Proficiency in API development, integration, and cloud-based automation solutions. Familiarity with databases, SQL, and data processing. Strong problem-solving skills and the ability to work in a fast-paced environment. Excellent communication skills and the ability to collaborate effectively with stakeholders. Experience with containerization and cloud platforms (AWS, Azure, GCP). Knowledge of DevOps practices and CI/CD pipelines. Familiarity with process mining and business process modelling techniques. Certifications in RPA, AI, or Low-Code platforms

Job Summary: We are seeking a skilled Generative AI Engineer with 2-3 years of experience to design, develop, and deploy cutting-edge generative AI models. You will work on creating AI systems for text, image, audio, or multimodal generation, fine-tuning LLMs (e.g., GPT, Claude, Llama), and optimizing models for performance and scalability. The ideal candidate has hands-on experience with deep learning frameworks, prompt engineering, and deploying AI solutions in production. Key Responsibilities: Develop, fine-tune, and optimize generative AI models (LLMs, diffusion models, GANs, etc.). Implement RAG (Retrieval-Augmented Generation) pipelines and improve model outputs. Work with transformers, LangChain, Hugging Face, PyTorch/TensorFlow , and other AI frameworks. Optimize models for latency, cost, and scalability in production environments. Collaborate with cross-functional teams (data scientists, product managers, engineers) to integrate AI solutions. Conduct experiments, A/B testing, and benchmarking to improve model performance. Stay updated on the latest advancements in generative AI, LLMs, and multimodal AI . Ensure ethical AI practices, including bias mitigation and responsible AI deployment. Qualifications & Skills: 2-3 years of hands-on experience in AI/ML, with a focus on generative AI . Strong proficiency in Python and AI frameworks like PyTorch, TensorFlow, or JAX . Experience with LLMs (GPT-4, Claude, Llama, Mistral) , fine-tuning, and prompt engineering. Familiarity with RAG, vector databases (Pinecone, FAISS), and model optimization techniques .

Must have: Gen AI, Agentic AI, Computer Vision, Tensorflow, Pytorch.. etc.. Proficiency in programming languages such as Python, with hands on experience in AIML libraries, Gen AI, Cloud ML, Vertex AI services and frameworks (e.g., TensorFlow, PyTorch, scikit-learn) Solid understanding of Gen AI, Agentic AI, Prompt engineering, AIML concepts, algorithms, and techniques. Experience with data preprocessing, feature engineering, and data visualization. Strong analytical and problem-solving skills, with the ability to analyze complex datasets and extract actionable insights. Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and experience deploying AIML models in cloud environments. Knowledge of software development practices, version control systems (e.g., Git), and agile methodologies. Excellent communication and collaboration skills to work effectively in cross-functional teams. Strong organizational and time management skills, with the ability to prioritize and manage multiple projects simultaneously. Good to have handson experience with NLP projects Responsibilities: Design and develop AIML models, algorithms, and applications to solve complex business problems. Collaborate with data scientists and subject matter experts to understand business requirements and translate them into AIML solutions. Implement and optimize AIML algorithms and models using programming languages such as Python, R, or Java. Conduct data preprocessing, feature engineering, and data exploration to ensure the availability of high-quality data for training and evaluation. Evaluate and benchmark different AIML models, frameworks, and tools to identify the most suitable solutions for specific use cases. Train, validate, and fine-tune AIML models using various techniques such as deep learning, reinforcement learning, and natural language processing. Deploy AIML models in production environments, ensuring scalability, performance, and reliability. Collaborate with software engineers to integrate AIML solutions into existing applications or develop new applications. Stay up-to-date with the latest advancements in AIML technologies, research papers, and industry trends. Provide technical guidance and support to junior team members and promote knowledge sharing within the COE team.

What is the Data and AI Team responsible for? We are building a growing Data and AI team. This team is responsible for building and managing data engineering, analytics, and GenAI solutions to drive business impact. We are looking for a pragmatic problem solver who thrives in a fast-paced environment and can deliver impactful solutions. The ideal candidate is a self-starter with a strong technical foundation, a collaborative mindset, and the ability to navigate complex data challenges. You will play a crucial role in integrating AI solutions in our existing digital solutions, optimizing our data infrastructure, and enabling insights through data#ASSOCIATE What are the ongoing responsibilities of AI/ML Senior Engineer? The AI/ML Engineer is responsible for researching and developing state-of-the-art generative AI tools and products. These tools aim to enhance the productivity and efficiency of our internal teams, specifically the sales, distribution, and operations teams. The role involves conducting extensive research and performing proof-of-concept work to validate the feasibility and effectiveness of AI models. The engineer will collaborate with cross-functional teams to integrate AI solutions seamlessly into existing workflows. Additionally, the AI/ML Engineer is expected to stay abreast of the latest advancements in AI and machine learning to ensure our solutions are cutting-edge and competitive. Research and Proof-of-Concept Work: The role includes a significant focus on research work to explore the potential of new AI technologies and methodologies. This involves experimenting with different algorithms and models to identify the most effective solutions for our needs. Proof-of-concept work is crucial to demonstrate the practicality and benefits of these AI solutions before full-scale implementation. Developing AI-powered tools: Design, implement, and maintain generative AI systems to support the needs of internal teams. Ensure these tools are scalable, reliable, and efficient for daily use. Conducting research: Regularly explore and analyze new AI trends and technologies to incorporate the latest advancements into our products. This includes reading research papers, attending conferences, and participating in industry forums. Proof-of-concept (PoC) work: Create PoCs to evaluate the feasibility and performance of different AI models. Use these PoCs to demonstrate the potential benefits to stakeholders and guide decision-making. Collaborating with teams: Work closely with sales, distribution, and operations teams to understand their needs and challenges. Tailor AI solutions to address specific pain points and improve overall efficiency. Data preprocessing and analysis: Clean, preprocess, and analyze large datasets to extract meaningful insights. Use these insights to train and optimize AI models. Documentation and reporting: Maintain comprehensive documentation of AI models, algorithms, and systems. Regularly report progress and results to stakeholders. Take ownership of projects, operating in a startup-like culture within an enterprise environment. What ideal qualifications, skills & experience would help someone to be successful? Bachelors degree in Computer Science, Data Science, Machine Learning, or a related field. A master’s or Ph.D. is preferred. Strong understanding of machine learning algorithms, deep learning frameworks, and statistical analysis. Proficiency in programming languages such as Python, R, or Java. Work Experience: 2-8 years of experience in AI/ML engineering or a related field. Proven track record of developing and deploying AI solutions in a production environment. Experience with data preprocessing, model training, and optimization techniques. Familiarity with cloud platforms and tools for AI/ML development and deployment. Strong problem-solving skills and the ability to work in a fast-paced, collaborative environment. Work Shift Timings - 2:00 PM - 11:00 PM IST

Job Title: Technical Writer API Documentation & Oxygen XML Job Location: Bangalore Experience: 5+ Years Job Description: We are looking for an experienced Technical Writer to join our team and take ownership of technical documentation, including API documentation, user guides, installation guides, and release notes . The ideal candidate will work closely with developers to standardize and enhance documentation quality while transitioning to advanced documentation tools. Key Responsibilities: Write clear, concise, and accurate documentation using Oxygen XML Author . Develop API documentation, user guides, installation guides, and release notes . Interpret technical specifications, developer notes, configuration files, and code to create end-user documentation. Ensure documentation is structured, accessible, and follows best practices. Work on documentation conversion to standardized tools (currently available in PDF/HTML only). Collaborate with cross-functional teams, including developers and product managers. Utilize AI/ML tools and techniques to enhance the documentation process. Manage multiple documentation projects simultaneously under time constraints. Required Skills: Oxygen XML Author (or similar XML editor) Experience with API Documentation Strong expertise in User Guides, Installation Guides, and Release Notes Understanding of AI/ML tools for enhancing documentation Knowledge of SDL Content Management System (preferred) Familiarity with Microsoft Office, Adobe PDF Editors Experience in online help, web help, PDFs, HTML-based documentation

AIML, SAP HANA with 2 implementation techno functional

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency. 2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems. 3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs. 4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment. 5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries. 6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills. 7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security. 8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 1. Programming Proficiency: Proficiency in Python, C++. Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products. 2. Data Handling Skills: Skilled in integrating, cleansing, and shaping data. Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB. 3. DevOps Experience: Experienced in DevOps practices. Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes). 4. Open-Source Contribution: Open-source Contribution is a plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks. 5. Problem-Solving Skills: Strong problem-solving and analytical skills. Experience in optimizing AI algorithms for performance and scalability. 6. AI Compiler/Runtime Skills: AI compiler/runtime skills would be a plus. 7. Agile Methodologies: Familiarity with Agile methodologies. Experience in Agile development of AI-based solutions. Ensuring efficient project delivery through iterative development processes Preferred technical and professional experience Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively. Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies. Proven ability to contribute to the development and improvement of AI frameworks and libraries. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.

1. Lead Development and deployment of AI frameworks, leveraging deep expertise in AI/ML and Data Science to ensure scalability, reliability, and efficiency. 2. Direct the implementation and optimization of machine learning algorithms, neural networks, and statistical modeling techniques, personally driving solutions for complex problems. 3. Personally oversee the development and deployment of AI solutions in production environments. 4. Collaborate closely with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, taking a hands-on approach to ensure seamless integration and efficiency. 5. Proactively stay abreast of the latest advancements in AI/ML technologies and actively contribute to the development and improvement of AI frameworks and libraries, leading by example in fostering innovation. 6. Effectively communicate technical concepts to non-technical stakeholders, showcasing excellent communication and interpersonal skills while leading discussions and decision-making processes. 7. Uphold industry best practices and standards in AI engineering , maintaining unwavering standards of code quality, performance, and security throughout the development lifecycle. 8. Demonstrate leadership in the use of container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, personally overseeing deployment strategies and optimizations. Required education Bachelor's Degree Preferred education Master's Degree Required technical and professional expertise 1. AI product development Leadership: - Deep experience in demonstrating coding skills, teaming capabilities, and end-to-end understanding of Enterprise AI product. - Deep background in machine learning, deep learning. - Expertise with product design, design principles and integration with various other enterprise products. - Strong skills in programing with C++, Python 2. Model Development Expertise: - Hands-on expertise with traditional machine learning, transformer-based and diffuser-based models (e.g., BERT, GPT, T5, Llama, Stable diffusion), showcasing mastery in model development and optimization. - Desirable experience in rigorously testing AI algorithms and models, ensuring robustness and reliability in real-world applications. 3. Traditional AI Methodologies Mastery: - Demonstrated proficiency in traditional AI methodologies, including mastery of machine learning and deep learning frameworks. - Familiarity with model serving platforms such as Triton inference server, TGIS and vLLM, with a track record of leading teams in effectively deploying models in production environments. - Proficient in developing optimal data pipeline architectures for AI applications, taking ownership of designing scalable and efficient solutions. 4. Development Ownership: - Proficient in backend C++, with hands-on experience integrating AI technology into full-stack projects. - Demonstrated understanding of the integration of AI tech into complex full-stack applications. 5. Problem-Solving and Optimization Skills: - Demonstrated strength in problem-solving and analytical skills, with a track record of optimizing AI algorithms for performance and scalability. - Leadership in driving continuous improvement initiatives, enhancing the efficiency and effectiveness of AI solutions. Preferred technical and professional experience 1. Knowledge in AI/ML and Data Science: - Over 13 years of demonstrated leadership in AI/ML and Data Science, driving the development and deployment of AI models in production environments with a focus on scalability, reliability, and efficiency. - Ownership mentality, ensuring tasks are driven to completion with precision and attention to detail. 2. Algorithm Implementation Mastery and Optimization: - Proven track record of hands-on implementation and optimization of machine learning algorithms, neural networks, and statistical modeling techniques, showcasing expertise in solving complex problems effectively. 3. Development of Large Language Models (LLMs): - Hands-on experience in the development and deployment of large language models (LLMs) in production environments, demonstrating proficiency in distributed systems, microservice architecture, and REST APIs. - Understanding the end-to-end development process of LLMs, from ideation to deployment, ensuring seamless integration into production workflows. 4. Commitment to Continuous Learning and Contribution: - Demonstrated dedication to continuous learning and staying updated with the latest advancements in AI/ML technologies. - Proven ability to contribute actively to the development and improvement of AI frameworks and libraries. 5. Effective Communication and Collaboration: - Strong communication skills, with the ability to effectively convey technical concepts to non-technical stakeholders. - Excellence in interpersonal skills, fostering collaboration and teamwork across diverse teams to drive projects to successful completion.

1. Utilize expertise in AI/ML and Data Science to develop and deploy AI models in production environments, ensuring scalability, reliability, and efficiency. 2. Implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems. 3. Hands-on experience in developing and deploying large language models (LLMs) in production environments, with a good understanding of distributed systems, microservice architecture, and REST APIs. 4. Collaborate with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment. 5. Stay updated with the latest advancements in AI/ML technologies and contribute to the development and improvement of AI frameworks and libraries. 6. Communicate technical concepts effectively to non-technical stakeholders, demonstrating excellent communication and interpersonal skills. 7. Ensure compliance with industry best practices and standards in AI engineering, maintaining high standards of code quality, performance, and security. 8. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments. Required education Bachelor's Degree Preferred education Bachelor's Degree Required technical and professional expertise 1. Programming Proficiency: Proficiency in Python, C++. Experience with relevant ML libraries (e.g., TensorFlow, PyTorch) for developing production-grade quality products. 2. Data Handling Skills: Skilled in integrating, cleansing, and shaping data. Expertise in various databases including open-source databases like MongoDB, CouchDB, CockroachDB. 3. DevOps Experience: Experienced in DevOps practices. Skills in Git, CI/CD pipelines (Jenkins, Travis CI, GitLab CI), and containerization (Docker, Kubernetes). 4. Open-Source Contribution: Open-source Contribution is a plus. Experience in contributing to open-source AI projects or utilizing open-source AI frameworks. 5. Problem-Solving Skills: Strong problem-solving and analytical skills. Experience in optimizing AI algorithms for performance and scalability. 6. AI Compiler/Runtime Skills: AI compiler/runtime skills would be a plus. 7. Agile Methodologies: Familiarity with Agile methodologies. Experience in Agile development of AI-based solutions. Ensuring efficient project delivery through iterative development processes Preferred technical and professional experience Proven ability to implement and optimize machine learning algorithms, neural networks, and statistical modeling techniques to solve complex problems effectively. Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in collaborating with cross-functional teams to integrate MLOps pipelines with CI/CD tools for continuous integration and deployment, ensuring seamless integration of AI/ML models into production workflows. Demonstrated commitment to staying updated with the latest advancements in AI/ML technologies. Proven ability to contribute to the development and improvement of AI frameworks and libraries. Strong communication skills with the ability to communicate technical concepts effectively to non-technical stakeholders. Demonstrated excellence in interpersonal skills, fostering collaboration across diverse teams. Proven track record of ensuring compliance with industry best practices and standards in AI engineering. Maintained high standards of code quality, performance, and security in AI projects. Experience in using container orchestration platforms such as Kubernetes to deploy and manage machine learning models in production environments, ensuring efficient scalability and management of AI infrastructure.

JioTesseract (Reliance Industries), India's biggest mixed reality company, is an MIT Media Lab spin-off and a public subsidiary of Reliance Industries Limited. We aim to democratize mixed reality by bringing meaningful AR/VR content and affordable devices for consumers to experience the power of the next wave of computing. The Product Manager - Software will be responsible for defining and managing the software product roadmap for our robotics solutions. This includes collaborating with cross-functional teams, from software engineers and designers to hardware teams, ensuring the successful design, development, and deployment of software features. You will play a key role in shaping the software strategy that powers the robots, focusing on system integration, user experience, AI/ML algorithms, and real-time control systems. Key Responsibilities Product Strategy & Roadmap : Define and prioritize the software product roadmap, aligning with overall company goals, customer needs, and market trends. Requirements Definition : Work with stakeholders (customers, engineers, and designers) to define software requirements, ensuring that the software meets the functional and non-functional needs of the robotic system. Cross-Functional Collaboration : Lead and collaborate with cross-functional teams, including software developers, hardware engineers, designers, and QA teams, to deliver high-quality software solutions. AI/ML Integration : Oversee the integration of AI/ML algorithms (e.g., computer vision, SLAM, autonomous navigation) into the software systems for robotics applications. Real-Time Systems : Ensure that the software supports real-time performance requirements for control, motion planning, and sensor integration within the robotics system. User Experience : Advocate for an intuitive and seamless user experience for robotic software, ensuring user interfaces (UI) and interactions are easy to understand and use. Software Testing & Validation : Define and implement software testing strategies, including unit tests, integration tests, and system-level validation. Ensure software stability, scalability, and security. Continuous Improvement : Analyze software performance metrics and feedback, continuously improving features, scalability, and overall product quality. Documentation : Maintain thorough and clear documentation for software specifications, technical requirements, and user-facing documentation. Agile Process Management : Use Agile methodologies (e.g., Scrum) to manage product development, track progress, and iterate on software features. Customer Feedback Loop : Gather user feedback from customers and end-users, ensuring that the software meets real-world use cases and pain points. Competitive Analysis : Keep up-to-date with the latest trends in robotics software, AI, and automation, analyzing competitors software offerings and identifying opportunities for differentiation. Risk Management : Identify and mitigate potential risks related to software development, including security vulnerabilities, software integration challenges, and scalability issues. Collaboration with Hardware Teams : Work closely with hardware teams to ensure seamless integration of software with hardware components, including sensors, actuators, and control systems. Required Skills & Qualifications Bachelors/Masters Degree in Computer Science, Robotics, Electrical Engineering, or a related field. 4+ years of experience in product management for software products, preferably in the robotics or AI industries. Strong experience in software development for real-time, embedded systems, particularly in robotics applications. Proficiency in programming languages such as C++ , Python , and experience with Robot Operating System (ROS) . Experience with AI/ML algorithms and computer vision (e.g., OpenCV, TensorFlow, PyTorch) for robotic applications. Understanding of robot control systems , motion planning , and SLAM (Simultaneous Localization and Mapping). Familiarity with cloud computing and edge computing for robotics data processing and storage. Experience with Agile methodologies (Scrum, Kanban) and using project management tools like Jira, Trello, or Asana. Familiarity with real-time operating systems (RTOS) and their application in robotics. Knowledge of software testing practices, including automated testing, integration testing, and system-level testing. Ability to work effectively in a cross-functional team environment , bridging the gap between hardware and software teams. Experience with version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) pipelines. Strong problem-solving skills and the ability to troubleshoot complex software and hardware integration issues. Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders. Proven ability to prioritize and manage multiple software development tasks simultaneously. Preferred Skills & Qualifications Experience with robotic simulation tools (e.g., Gazebo, Webots, V-REP). Familiarity with Docker and containerization technologies. Experience with cloud-based robotics platforms (e.g., AWS RoboMaker, Microsoft Azure). Knowledge of cybersecurity principles, especially for robotics applications. Previous experience in startup environments or working in an agile, fast-paced team . Knowledge of UX/UI design principles, specifically for robotic software systems. Master's degree in a related field is a plus. Personal Attributes Strong leadership skills, with a collaborative, team-oriented approach to product management. Detail-oriented with the ability to balance competing priorities in a fast-paced, dynamic environment. Self-starter who thrives in an innovative, technology-driven industry. Passionate about robotics, AI, and creating impactful software products that solve real-world problems. Excellent time management and organizational skills .

Develop and implement AI/ML models to solve real-world problems. Design and optimize NoSQL and RDBMS databases for AI applications. Develop and integrate AI-powered REST APIs for seamless application functionality.

Level/Seniority: Senior Years of Experience: 10+ years total, 3+ years in AI products Responsibilities: • Define and manage AI product vision, roadmap, and delivery strategy. • Own Agile backlog prioritization, sprint planning, and stakeholder alignment. • Ensure successful delivery and integration of AI products into business processes. Required Skills: • Strong Agile methodology knowledge (Scrum, Kanban). • Solid understanding of AI/ML product lifecycle and development. • Exceptional stakeholder management and communication. Nice to Have: • Certified Scrum Product Owner (CSPO). • Background in analytics or data-driven products. Education: • Bachelor's/Masters in Business, IT, or related field.

Primary Responsibilities: Model Deployment: Design, code, and implement software solutions that deploy GENAI models like RAG, Agentic workflows, AI agents into production environments, ensuring scalability and reliability Data Analysis: Investigate and analyze large-scale computing frameworks and data analysis systems to derive actionable insights Stakeholder Communication: Clearly present complex analytics results and concepts to leadership and internal stakeholders, facilitating informed decision-making Cloud Development: Develop and deploy robust data pipelines and machine learning models on cloud platforms such as Azure, AWS, GCP, and Databricks, ensuring optimal performance and security AI/ML Techniques: Employ advanced AI and ML techniques, including natural language processing (NLP), natural language understanding (NLU), semantic understanding, intent classification, computer vision, deep learning, and automatic speech recognition (ASR) Deep Learning Applications: Apply deep learning technologies to enable systems to visualize, learn, and respond to complex scenarios effectively. Interactive Experiences: Adapt machine learning methodologies for applications in artificial intelligence, robotics, and other interactive user experiences Model Observability: Utilize model observability tools to gain insights into the behavior, performance, and health of deployed ML models, including tracking, alerting, and compliance monitoring MLOps Skills: Implement best practices in machine learning operations (MLOps) to streamline workflows and enhance collaboration 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

About Position: GenAi- you'll design and implement scalable, secure, and high-performance architectures for Generative AI applications, optimizing algorithms, models, and systems for intelligent decision-making and automation Role: GenAI Architect Location: Any PSL Location Experience: 10- 15 years Job Type: Full Time Employment What You'll Do: This role requires a strong understanding of various AI/ML models, including deep learning, and proficiency in building and deploying them on cloud Develop and implement AI/ML models using Python, including experience building Flask endpoints. Leverage cloud resources, including Vertex AI, for model training, deployment, and integration. Demonstrate expertise in embeddings, prompt engineering, and RAG (Retrieval-Augmented Generation) application development. Collaborate effectively with cross-functional teams, presenting technical findings and solutions clearly. Please mention brief description What You'll Do. 8+ years of experience in AI/ML and good hands on experience in Gen AI(2+ Yrs.) Proven experience in building and deploying ML models on GCP. Strong proficiency in Python and Flask framework. Expertise You'll Bring: Deep understanding of various AI/ML models, including deep learning. Experience in embeddings, Vertex AI, and prompt writing. Experience with RAG application development and its working principles. Excellent communication and presentation skills Please mention brief description Expertise You'll Bring. Knowledge of NLP (Natural Language Processing) and related techniques. Familiarity with data visualization and analysis tools. Benefits: Competitive salary and benefits package Culture focused on talent development with quarterly promotion cycles and company-sponsored higher education and certifications Opportunity to work with cutting-edge technologies Employee engagement initiatives such as project parties, flexible work hours, and Long Service awards Annual health check-ups Insurance coverage: group term life, personal accident, and Mediclaim hospitalization for self, spouse, two children, and parents Inclusive Environment: Persistent Ltd. is dedicated to fostering diversity and inclusion in the workplace. We invite applications from all qualified individuals, including those with disabilities, and regardless of gender or gender preference. We welcome diverse candidates from all backgrounds. We offer hybrid work options and flexible working hours to accommodate various needs and preferences. Our office is equipped with accessible facilities, including adjustable workstations, ergonomic chairs, and assistive technologies to support employees with physical disabilities. If you are a person with disabilities and have specific requirements, please inform us during the application process or at any time during your employment. We are committed to creating an inclusive environment where all employees can thrive. Our company fosters a values-driven and people-centric work environment that enables our employees to: Accelerate growth, both professionally and personally Impact the world in powerful, positive ways, using the latest technologies Enjoy collaborative innovation, with diversity and work-life wellbeing at the core Unlock global opportunities to work and learn with the industry's best Let's unleash your full potential at Persistent "Persistent is an Equal Opportunity Employer and prohibits discrimination and harassment of any kind."

Job Title S&C GN AI Managed service Data Operations Analyst Management Level:11 Analyst Location:Hyderabad Must have skills:Python, Pyspark, Databricks, AI/ML Good to have skills:cloud platforms like AWS, Azure, or Google Cloud for deploying and scaling language models, Exposure to Retail, Banking, Healthcare projects. Job Summary : An opportunity to work on high-visibility projects with top clients around the globe. Potential to Co-create with leaders in strategy, industry experts, enterprise function practitioners, and business intelligence professionals to shape and recommend innovative solutions that leverage emerging technologies. Ability to embed responsible business into everything"from how you service your clients to how you operate as a responsible professional. Personalized training modules to develop your strategy & consulting acumen to grow your skills, industry knowledge, and capabilities. Opportunity to thrive in a culture that is committed to accelerating equality for all. Engage in boundaryless collaboration across the entire organization. Roles & Responsibilities: As a Data Operations Analyst, you would be responsible to ensure our esteemed business is fully supported in using the business-critical AI enabled applications. This involves solving day-to-day application issues, business queries, addressing adhoc data requests to ensure clients can extract maximum value for the AI applications. Debug issues related to data loads, batch pipeline, application functionality including special handling of data/batch streams. Monitor and maintain pre-processing pipelines, model execution batches and validation of model outputs. In case of deviations or model degradation, take up detailed root cause analysis and implement permanent fixes. As a Data Operations Analyst, you would be working on initial triaging of code related defects/issues, provide root cause analysis and implement code fix for permanent resolution of the defect. Design, build, test and deploy small to medium size enhancements that deliver value to business and enhance application availability and usability. Responsible for sanity testing of use cases as part of pre-deployment and post-production activities. Primarily responsible for Application availability and stability by remediating application issues/bugs or other vulnerabilities. Data Operations Analysts evolve to become Subject Matter Experts as they mature in servicing the applications. Professional & Technical Skills: Bachelor's or Master's degree in any engineering stream or MCA. Experience/Education on Statistics, Data Science, Applied Mathematics, Business Analytics, Computer Science, Information Systems is preferable. Proven experience (2+ years) in working as per the above job description is required. Exposure to Retail, Banking, Healthcare projects is added advantage. Proficiency and hands-on experience in Data Engineering technologies like Python, R, SQL, Spark, Pyspark, Databricks, Hadoop etc. Ability to work with large data sets and present findings/insights to key stakeholders; Data management using databases like SQL. Experience with any of the cloud platforms like AWS, Azure, or Google Cloud for deploying and scaling language models. Experience with any of the data visualization tools like Tableau, Qlikview, and Spotfire is good. Knowledge on PowerBI & PowerApps is an added advantage. Excellent analytical and problem-solving skills, with a data-driven mindset. Proficient in Excel, MS Word, PowerPoint, etc. Ability to solve complex business problems and deliver client delight. Strong writing skills to build points of view on current industry trends. Good Client handling skills; able to demonstrate thought leadership & problem-solving skills. Qualifications Experience:Minimum 2+ year(s) of experience is required Educational Qualification:B.Tech/BE or MCA

Role & responsibilities Primary Role s Responsibilities: The primary role of the candidate will be: • Apply machine learning and computer vision techniques for object classification, detection, recognition, and segmentation. • Design, develop, train, validate, and deploy neural networks and machine learning models for computer vision applications. • Utilize tools such as Python, R, Flask, NumPy, Pandas, NLTK, SciPy, TensorFlow, Keras, PyTorch, and OpenCV for model development. • Build and fine-tune deep learning, machine learning, and reinforcement learning models for various tasks. • Develop models on image, video, and audio data for classification, detection, recognition, and segmentation using transformers and algorithms. • Evaluate model performance using metrics such as accuracy, precision, recall, F1-score, and AUC, addressing overfitting/underfitting issues. • Build APIs for AI-ML models, implement MLOps, and automate processes. • Stay updated with new AI/ML technologies and innovations. • Utilize software development and agile methodologies. • Develop Python solutions in a Linux environment. • Work with databases such as MySQL/PostgreSQL and cloud-native databases. • Implement data warehouse solutions on cloud platforms. Working Experience and Qualification: Education: Masters degree in computer science/Information Technology with demonstrated experience in AI-ML. Experience: 5-9 years of work experience in AI-ML. Proven experience in object detection and video analytics, preferably using YOLO or similar frameworks. Experience in deploying models using ML frameworks like YOLO, TensorFlow, and PyTorch. \ Skills: Expertise in Python, R programming, and AI-ML tools. Hands-on experience with platforms like OpenAI and Azure. Knowledge of microservices deployment using Linux/Kubernetes (Azure Kubernetes Service). Experience with NLP/Transformers-based models for data analytics and optimization

Mandatory Skills - Skill:-Python, API dev, enterprise chatbot, AI/ML + Git, CI/CD, SDLC, and Agile Role and Responsibilities: Develop and Deploy Chatbots: Build, test, and deploy intelligent chatbots using Python, integrating machine learning (ML) and natural language processing (NLP) algorithms to enhance user interaction. NLP Model Integration: Design and implement NLP models to understand user intents, entities, and context, ensuring high-quality user experiences and meaningful conversations. Data Preprocessing & Cleaning: Collect, clean, and preprocess datasets used for training the chatbot, ensuring the data is ready for ML model development. Collaborate with Cross-functional Teams: Work with product managers, UX/UI designers, and backend developers to create effective conversational flows and integrate chatbots into existing systems or applications. Model Optimization & Fine-tuning: Continuously evaluate and optimize NLP models for performance, accuracy, and user satisfaction. Monitor & Maintain Chatbot Performance: Set up monitoring systems to track chatbot performance, analyze user feedback, and make improvements based on insights. Stay Updated on Latest Trends: Research and stay updated on the latest advancements in AI, NLP, and ML techniques related to chatbot development. Required Skills & Qualifications: Proficiency in Python: Strong experience with Python programming, particularly for AI/ML development (NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.). NLP Knowledge: Solid understanding of NLP concepts and tools (spaCy, NLTK, Hugging Face, etc.) for developing conversational agents. Machine Learning Experience: Hands-on experience with building and training ML models, particularly in the context of NLP (e.g., text classification, sentiment analysis, sequence-to-sequence models). Deep Learning Expertise: Familiarity with deep learning models like transformers, RNNs, and BERT for chatbots and NLP tasks. Data Processing Skills: Experience in cleaning, preprocessing, and preparing text data for machine learning tasks. Chatbot Frameworks & Tools: Familiarity with chatbot development frameworks (e.g., Rasa, Dialogflow, Microsoft Bot Framework) and chatbot deployment platforms. Version Control: Experience with Git for version control and collaboration. Preferred Qualifications: Experience with Cloud Platforms: Familiarity with cloud services (AWS, Azure, Google Cloud) for deploying ML models and chatbots. Knowledge of API Integration: Ability to integrate chatbots with external APIs for enriched interactions (e.g., payment systems, CRM). Experience with Multilingual Chatbots: Knowledge of handling multilingual chatbots or language translation models is a plus.

Job Summary: We are seeking an experienced Account Manager Sales to join our sales team. The ideal candidate will be responsible for encompassing a variety of responsibilities aimed at driving sales growth and managing client relationships within IT Cloud Services. We're looking for someone with 6-8 years of experience, primarily focused on hunting new logos and expanding client bases in the IT services space. If you have a strong background in IT sales, managed services, staff augmentation, and digital transformation (ADMS), this might be a great fit for you! Key Responsibilities: Drive New Client Acquisition : Lead the charge in identifying and acquiring new clients across industries. Generate new sales using existing and potential customer networks. Sales Leadership : Develop strategies to push growth in managed services, IT staff augmentation, and digital transformation solutions. Market Leadership : Stay ahead of industry trends and bring innovative solutions to meet clients' evolving needs. End-to-End Sales Ownership : From lead generation to contract closure, take full ownership of the sales cycle. Build relationships : Develop and maintain long-term relationships with clients. Build and maintain relationships with clients, oversee sales, and achieve sales targets. Handle customer needs, resolve disputes, and make recommendations to improve sales performance. Handle customer needs : Address client needs and provide effective solutions to disputes. Set sales targets : Set sales targets and KPIs, and make regular reports on sales performance. Set and track sales account targets, aligned with company objectives. Improve sales : Make recommendations to improve sales performance. Oversee account representatives : Oversee account representatives to boost sales. Negotiate contracts : Negotiate contracts with clients. Understand sales performance : Understand sales performance metrics and how to deliver a good customer experience. Monitor sales metrics (e.g. quarterly sales results and annual forecasts) and supervise account representatives to ensure sales increase. Manage a portfolio of accounts to achieve long-term success. Generate new business using existing and potential customer networks. Resolve conflicts and provide solutions to customers in a timely manner. Report on the status of accounts and transactions. Suggest actions to improve sales performance and identify opportunities for growth. Stay on top of accounts, making sure they receive services that are within their budget and meet their needs. Meet regularly with other team members to discuss progress and find new ways to improve business. Generate progress reports for clients and senior leaders within the organization. Identify upsell, cross-sell, and renewal opportunities and communicate with the sales team regularly. Devising campaign ideas and handling their management and execution. Leading a team of sales professionals and training them. Ensure team members have adequate resources to reach their sales targets. Reviewing customer feedback to identify areas for improvement. Establishing sales territories for an organization. Presenting campaign updates and statistics to key stakeholders. Qualifications: Education and Experience: Bachelor's or Master degree in Business Administration, Sales & Marketing, Information Technology, Computer Science, or a related field. 5-8 years of experience as an Account Manager Sales, preferably in the IT Cloud Services industry. Skills: Excellent communication, negotiation and interpersonal skills, with the ability to interact effectively with technical and non-technical stakeholders. Problem-solving and critical thinking skills. Experience managing large account portfolios. Knowledge of CRM software (Salesforce, Zoho, etc) and MS Office. Understanding of sales performance metrics. Good organizational skills and attention to detail. Proven work experience as a Sales Account Manager or Sales Account Executive. Hands on experience in sales and an ability to deliver excellent customer experience. An ability to deliver projects and answer inquiries on time. Business acumen with a problem-solving attitude. Internship or professional experience in a sales or customer service role. Ability to multitask and juggle several responsibilities simultaneously. Excellent organizational skills and attention to details. Proven track record of meeting or exceeding quotas and receiving positive customer feedback. Proficiency with common customer success and customer relationship management software, such as Gainsight and Salesforce. Good to have professional certification (ex: from Strategic Account Management Association)

Java SDET with experience in J2EE, React, and exposure to GenAI/Agentic AI/LLM models to join our team.candidate will have expertise in enterprise-level web application development and a strong understanding of AI-driven technologies.

Only candidates currently in Bihar or Open to relocate to Bihar, please apply: This is an exciting opportunity for an experienced industry professional with strong expertise in artificial intelligence and machine learning to join and add value to a dedicated and friendly team. We are looking for an AIML Engineer who is passionate about developing AI-driven technology solutions. As a core member of the Development Team, the candidate will take ownership of AI/ML projects by working independently with little supervision. The ideal candidate is a highly resourceful and skilled professional with experience in applying AI to practical and comprehensive technology solutions. You must also possess expertise in machine learning, deep learning, TensorFlow, Python, and NLP, along with a strong understanding of algorithms, functional design principles, and best practices. You will be responsible for leading AI/ML initiatives, ensuring scalable and optimized solutions, and integrating AI capabilities into applications. Additionally, you will work on REST API development, NoSQL database design, and RDBMS optimizations. Key Responsibilities: Develop and implement AI/ML models to solve real-world problems. Utilize machine learning, deep learning, TensorFlow, and NLP techniques. Lead AI-driven projects with program leadership, governance, and change enablement. Apply best practices in algorithm development, object-oriented and functional design principles. Design and optimize NoSQL and RDBMS databases for AI applications. Develop and integrate AI-powered REST APIs for seamless application functionality. Collaborate with cross-functional teams to deliver AI-driven solutions. Stay updated with the latest advancements in AI and ML technologies. Candidate Profile: Required Qualifications: Qualification: Bachelors or Masters degree in Computer Science or a related field. Minimum 2 years of experience in AI/ML application development. Strong expertise in machine learning, deep learning, TensorFlow, Python, and NLP. Experience in program leadership, governance, and change enablement. Knowledge of basic algorithms, object-oriented and functional design principles. Experience in REST API development, NoSQL database design, and RDBMS optimization. Excellent problem-solving skills and attention to detail. Strong communication and collaboration skills.

Position: Software Engineer (AI/ML) Qualification: B.E./B.Tech/M.E./M.Tech Responsibilities: Study and transform data science prototypes Designing Machine Learning systems and self-running Artificial Intelligence (AI) software to automate predictive models Research and implement appropriate ML algorithms and tools Develop Machine Learning applications according to requirements Select appropriate datasets and data representation methods Run Machine Learning tests and experiments Perform statistical analysis and fine-tuning using test results Train and retrain systems when necessary Extend existing ML libraries and frameworks Keep abreast of developments in the field Required Skills/Abilities: 2 4 years experience in AI/ML Good knowledge of Data Structures and Algorithms, and Mathematical Aptitude Excellent programming skills in Python and basic libraries for Machine Learning such as scikit-learn and pandas Must have a very good understanding of AI/ML algorithms and methods Prior knowledge of MLOps tools and Deep Learning methods and tools like PyTorch, Keras, or TensorFlow is preferable Good communication and people management skills with some experience of client handling Reporting To: Lead Software Engineer/Project Manager

Position: Edge AI Engineer - Cancard Inc Location: New Delhi / Toronto Role Type: Full Time Cancard Inc and Advaa Health are seeking an experienced, engaged, and hands-on healthcare industry Edge Computing / IOT / CV expert for the role of Edge AI Engineer. This role will be pivotal in driving development, launch, and successfully commercializing an innovative portfolio of digital healthcare products for global markets. Cancard Inc has been a multi-technology company based in Markham (Toronto) since 1989. Both Cancard and its sister company, Advaa Health, are at the forefront of transforming primary healthcare through technological innovation. Our mission is to empower primary care physicians with state-of-the-art digital tools and solutions that streamline their practices and significantly reduce administrative burdens and operational costs. Amidst increasing paperwork and complex administrative tasks faced by healthcare professionals, we serve as a key partner, enabling physicians to focus on patient care. Our healthcare product portfolio leverages cutting-edge technologies in data analytics, artificial intelligence, and cloud computing to offer seamless, intuitive, and cost-effective solutions. By integrating our systems, primary care practices can enhance patient engagement, optimize appointment scheduling, automate billing and coding processes, and access comprehensive patient health records in real-time. These advancements not only improve the quality of care provided but also contribute to a significant reduction in overhead costs. This position offers a unique opportunity for AI Engineers who are passionate about solving critical healthcare challenges to learn and grow within the company. The role provides direct experience and exposure to customers in the US, Canada, and other global markets. KEY RESPONSIBILITIES: EDGE COMPUTING MODEL DEPLOYMENT: Convert, optimize, and deploy trained AI/ML models for edge inference using tools such as: TensorRT (for NVIDIA Jetson and GPUs) ONNX Runtime (for hardware-agnostic and cross-platform deployment) OpenVINO (for Intel-based edge devices) TFLite (for mobile and microcontroller-based healthcare applications) Apply model optimization techniques including: Post-training quantization (INT8, FP16) Pruning and weight clustering Model conversion to ONNX or IR formats for interoperability Benchmark models for: Latency, Throughput, Memory Footprint, and Power Efficiency Profile and debug model performance using tools such as: NVIDIA Nsight, TensorRT Profiler, Intel DevCloud, Netron, or Edge TPU Compiler Integrate AI inference engines with real-time edge pipelines, ensuring low-latency decision-making in clinical or diagnostic environments. IOT SENSOR INTEGRATION: Integrate and interface with a wide range of biomedical and motion sensors commonly used in healthcare devices: Inertial Measurement Units (IMUs): Accelerometers, gyroscopes, magnetometers. Physiological Sensors: Heart rate (PPG), SpO2, ECG, EMG, temperature, respiration, and blood pressure sensors. Environmental Sensors: CO, humidity, light exposure (for ambient health monitoring). Sensor Communication Protocols: Work with IC, SPI, UART, BLE (Bluetooth Low Energy), and USB HID for data acquisition and transmission. Implement sensor drivers, data parsing, and calibration routines for real-time use. Data Fusion & Preprocessing: Apply filtering (Kalman, low-pass, high-pass) and sensor fusion algorithms to combine multiple sensor modalities for robust signal interpretation. Normalize and preprocess raw sensor data for efficient input into ML models. Time-Series Analysis: Manage high-frequency data streams and maintain synchronization across multiple sensors. www.cancard.com Build and deploy real-time AI pipelines for activity recognition, fall detection, gait analysis, and anomaly detection in patient vitals. Edge Implementation: Run lightweight signal processing and classification models directly on microcontrollers or edge devices. Use platforms such as TinyML, Edge Impulse, or CMSIS-NN for embedded ML on sensor data. Device Interoperability & Testing: Ensure compatibility with commercial wearable platforms (e.g., smart bands, chest straps, ECG patches). Conduct in-field testing and validation in collaboration with clinical or biomedical teams. COMPUTER VISION EXPERTISE: Strong experience developing and deploying computer vision models for edge devices (e.g., object detection, segmentation, classification, pose estimation). Proficient with deep learning architectures used in computer vision, such as CNNs, MobileNet, EfficientNet, YOLO, U-Net, and Vision Transformers (ViT). Hands-on experience with optimizing CV models for performance on resource-constrained devices (e.g., quantization, pruning, knowledge distillation). Experience using OpenCV and other image processing libraries in Python and/or C++ Familiarity with real-time video analytics, multi-frame inference, and hardware-accelerated vision pipelines. Understanding of image preprocessing techniques for low-quality or noisy medical data (e.g., denoising, contrast enhancement, resizing). Experience integrating camera systems and working with edge hardware with GPU/TPU/ISP acceleration. DEEP LEARNING EXPERTISE (Preferred): Solid experience designing and implementing deep learning models for edge deployment, with emphasis on applications in hospital environments. Knowledge of developing and optimizing models using Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) and Long Short-Term Memory (LSTM). Transformers and attention-based architectures (e.g., Temporal Fusion Transformers, Vision Transformers) for capturing long-range dependencies in sequential health data. Experience deploying deep learning models on edge inference platforms (e.g., TensorFlow Lite, ONNX Runtime, NVIDIA TensorRT, OpenVINO). Strong understanding of latency, throughput, and memory trade-offs in edge scenarios, especially for real-time clinical decision support. MODEL OPTIMIZATION & DEPLOYMENT: Design, optimize, and deploy machine learning models for real-time inference on edge devices in clinical and hospital environments. Implement quantization, pruning, and compression techniques to ensure efficiency on resource-constrained platforms. Port AI models to run on hardware such as NVIDIA Jetson, Intel Movidius, ARM Cortex-M, or custom medical edge hardware. HEALTHCARE INDUSTRY SOLUTIONS: Work on edge AI solutions in medical imaging (e.g., X-ray, CT, MRI), patient vitals monitoring, telemedicine devices, and wearable health trackers. Ensure models comply with healthcare standards, data formats such as DICOM, HL7, and FHIR. Integrate AI into point-of-care diagnostics, clinical decision support systems, or edge-assisted robotic surgeries. SOFTWARE & HARDWARE INTEGRATION: Interface with camera modules, biosensors, and physiological data sources (e.g., ECG, SpO2). Build low-latency pipelines that support real-time analysis in mission-critical use cases. Collaborate with hardware engineers to ensure compatibility and performance across different boards and chipsets. VALIDATION & COMPLIANCE: Ensure solutions meet regulatory requirements (e.g., FDA, CE, ISO 13485, IEC 62304). Collaborate on validation protocols, clinical testing, and explainability in AI decisions for medical accountability. CROSS-FUNCTIONAL COLLABORATION: Work closely with data scientists, clinical SMEs, software engineers, QA testers, and others. Document all processes for traceability and regulatory submission. QUALIFICATIONS: Education: Bachelors or Master’s degree in Computer Science, Electronics, or related fields. Technical Skills: ML Frameworks: PyTorch, TensorFlow, Keras, ONNX. Edge Tools: TensorRT, TFLite, OpenVINO, TVM. Programming Languages: Python, C++, C. Embedded Experience: Linux-based OS (Yocto, Ubuntu), RTOS, and edge platforms (Jetson, NXP i.MX, Intel NUC, Coral). Medical Data Standards: Exposure to DICOM, HL7, FHIR Hardware Acceleration: CUDA, OpenCL, ARM NN, DSP/TPU integrations. Device Communication: Bluetooth LE, USB, UART, SPI, I2C for connecting medical peripherals. Security & Privacy: Familiarity with HIPAA, data encryption, secure firmware update practices. Soft Skills: Passion for healthcare innovation. Ability to translate clinical requirements into technical solutions. Clear and concise documentation and communication. Strong ownership and a proactive, detail-oriented mindset. Preferred Qualifications: Experience developing AI for digital pathology, radiology, or wearable health devices. Familiarity with clinical workflows and hospital IT systems (PACS/RIS). Hands-on experience in federated learning or on-device learning for privacy-preserving AI. Prior involvement in FDA/CE Class II or III device development lifecycle. WHAT WE OFFER: Competitive salary and benefits package. Flexible working hours. A dynamic and supportive work environment with opportunities for professional growth and development. The chance to work on meaningful projects that have a real impact on healthcare. HOW TO APPLY: Please submit your resume, cover letter, and any relevant work samples or project portfolios to HR@cancard.com. In your cover letter, explain why you're interested in this role and how your background and experience make you a good fit for our team. We thank all applicants for their interest in joining Cancard, but only those selected for an interview will be contacted. Cancard is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Role & responsibilities Preferred candidate profile Perks and benefits

Job Description: Technical Manager Company: Karini AI Location: Pune (Wakad) Experience Required: 6 - 11 years About Us: At Karini AI, we enable businesses to harness the power of Generative AI effortlessly, freeing them from skill and infrastructure development complexities. Our cutting-edge platform lets you quickly turn your innovative ideas into reality, transforming them from initial concepts to full production within minutes. Designed with stringent enterprise-level security and governance, along with robust AI safety measures, Karini AI meets the most demanding compliance standards. Our platform provides access to the latest in Large Language Models (LLMs) and a versatile experimentation environment, ensuring flexibility and top-tier quality to build user trust. We offer detailed operational dashboards to track Generative AI usage, performance, and trends and manage costs effectively. Staying at the forefront of scientific advancement and the evolving landscape of models, Karini AI eliminates technical debt. Our no-code approach to Generative AI application deployment ensures you dont compromise on quality or speed when bringing products to market. Karini AI is adaptable and perfect for various applications, including virtual assistants, text generation, summarization, Q&A, semantic search, classification, and image creation. #Kariniai Role Overview: We seek a dynamic Technical Manager with a strong technical background and proven experience managing high-performing product software engineering teams. You will play a pivotal role in leading the development of innovative software products while ensuring excellence in execution. You will directly report to the Ex-Amazon founding team to learn from the best and be part of the fastest growing disruptor. Key Responsibilities: Team Leadership: Manage, mentor, and grow a team of software, QA, and AI engineers. Foster a culture of collaboration, innovation, and continuous learning. Technical Ownership: Oversee the architecture and development of full-stack applications, microservices, and Python-based systems. Provide technical guidance and ensure the implementation of best practices in coding, architecture, and scalability. Product Development: Drive the development and delivery of software products from conception to deployment. Collaborate with cross-functional teams, including Product Management, Data Science, and QA, to define and execute product roadmaps. Agile Practices: Champion Agile methodologies and ensure effective use of tools like Jira for sprint planning, tracking, and reporting. Optimize workflows to enhance productivity and transparency. Generative AI and Machine Learning Integration: Leverage expertise or interest in Generative AI and Machine Learning to contribute to product innovation. Partner with AI/ML teams to integrate advanced features into software solutions. Hybrid Collaboration: Coordinate and align with hybrid teams across different time zones. Maintain effective communication channels to ensure seamless collaboration. Key Qualifications: Experience: 5+ years of experience managing software engineering teams with 6+ years of overall experience in Software development. Proven track record in building and delivering scalable software products. Technical Skills: Expertise in full-stack development, microservices architecture, and Python programming. Mastery of Agile methodologies and Jira. Strong system design and architectural skills in AWS, Azure or GCP cloud Soft Skills: Excellent communication, leadership, and decision-making skills. Ability to manage hybrid teams effectively. Advantageous Skills: Knowledge of Generative AI, Machine Learning, and related technologies. Familiarity with cloud platforms such as AWS, Azure, or GCP. Education Qualification: Mandatory: Bachelor of Engineering in Computer Science, Information Technology, or any other engineering discipline. Preferred: M.Tech, M.E. & B.E. Computer Science Why Join Us? Work with the Ex-Amazon Founder Team directly to disrupt the industry Employee Benefits such as Medical Insurance, Flexible work culture, and participation in company stock units Work on innovative AI-driven products that solve complex problems. Collaborate with a talented and passionate team in a dynamic environment. Opportunities for professional growth and skill enhancement in Generative AI A supportive, inclusive, and flexible work culture that values creativity and ownership.

Technical Needs: 5+ years experience in Python Hands-on experience in Generative AI, LLMs, RAG Pipeline, prompt tuning, Agentic frameworks like LangChain/LangGraph Must have good experience on AWS and Docker based development. Good to have knowledge of Hugging Face, agentic frameworks, and Machine Learning Job Responsibilities: The responsibilities will depend on the needs of your organization and team, but edit these to get you started: Model, build, and test AI software to ensure it can take on large swaths of data and achieve desired results. Use Python, JavaScript, and C++ to create a faster, more capable AI. Analyze statistics, data, and algorithms for projection accuracy. Use AI analysis to make strategy recommendations that align with company goals. Work with a team of machine-learning and data engineers to ensure seamless AI development and integration. Stay current on AI knowledge, trends, and regulations. Collect, organize, and present progress with team leadership and stakeholders.