3 Neural Architectures Jobs

At Fujitsu AI Lab, we are pioneers in research, innovation, and product development within the realms of AI (artificial intelligence), Machine Learning (ML), and Data Science. Our cutting-edge technologies are seamlessly integrated into Fujitsu's products and customer systems, spanning diverse sectors such as finance, telecommunications, manufacturing, healthcare, and social infrastructure. Committed to driving the future forward, we focus on groundbreaking AI research in areas like Generative AI, Cognitive AI, Graph ML, and ML models for complex temporal and multimodal data. As an AI-Researcher at Fujitsu, you will play a pivotal role in leading innovative research that aligns with our AI strategy. Your contributions will directly impact product innovations and the exploration of novel AI technologies. In addition to driving scientific exploration, you will have the opportunity to publish in top-tier conferences and journals, as well as secure patents for your innovative work. Your responsibilities as an AI-Researcher will encompass a range of technical skills, including: - Advanced AI/ML Expertise: Demonstrating a deep understanding of theoretical machine learning, statistical learning theory, and practical implementation across various domains. - Stay updated with the latest AI algorithms & neural architectures and their application in discriminative and generative models, explainable AI, causal reasoning, knowledge representation, and more. - Proficiency in AI/ML Programming: Showcasing advanced coding skills, working with AI/ML libraries, and familiarity with major AI platforms and tools. - Strong publication track record in top-tier conferences and journals, particularly in the field of computer vision. In your role as a Researcher, you will also be expected to: - Identify and Frame Research Problems: Collaborate with fellow researchers to scope new projects, identify critical challenges, and develop innovative solutions. - Develop Advanced Technologies: Design new algorithms, neural architectures, and computing methodologies and validate them through theoretical and experimental research. - Conduct Rigorous Data Analysis: Collect and analyze data to draw inferences, support proposed solutions, and demonstrate practical applications. Furthermore, you will engage in collaboration, knowledge sharing, and industry impact by: - Sharing key findings with internal leadership and stakeholders. - Drafting and submitting patents, authoring research papers for prestigious AI/ML/CV/NLP conferences and journals. - Engaging with academic institutions and collaborators to expand Fujitsu's network and promote cutting-edge AI research. - Collaborating closely with applied researchers to transform scientific discoveries into practical solutions and support technology transition. We expect you to demonstrate scientific leadership, exceptional communication skills, adaptability, and a growth mindset. A Ph.D. in AI, Machine Learning, Computer Science, or related fields, along with 3-10 years of research experience post-PhD, is required for this role. Candidates with more experience will be considered for suitable positions.,

Key Skills: AI/ML Research, Algorithm Design, Neural Architectures, Data Analysis, AI/ML Libraries, Natural Language Processing, Computer Vision, Multi-modal Data Analytics, Research Publications, Patents, Academic Collaboration, Communication Skills, Scientific Leadership Roles & Responsibilities: Identify and frame new research projects by brainstorming with other researchers to scope critical research challenges and develop innovative solutions. Design new algorithms, neural architectures, and computing methodologies through theoretical and experimental research. Conduct rigorous data analysis to support proposed solutions and demonstrate their practical applications. Share key findings with internal leadership, including Project Leaders, Research Managers, and Project Directors. Draft and submit patents, and author research papers for prestigious AI/ML/CV/NLP conferences and journals. Engage with academic institutions and collaborators to expand 's network and promote cutting-edge AI research. Collaborate with applied researchers to transform core scientific discoveries into practical solutions. Facilitate the transfer of research outcomes to business units and external clients, driving real-world impact. Lead scientific projects towards impactful breakthroughs. Translate complex research into understandable and actionable insights through exceptional communication, report writing, and presentation skills. Willingness to learn new fields, explore uncharted territories in AI, and develop cross-disciplinary skill sets. Experience Requirement: 4-7 years of research experience post-PhD in AI, Machine Learning, Computer Science, or a related field. Advanced expertise in AI/ML, with a deep understanding of machine learning, statistical theory of learning, and AI concepts and their practical application in domains like natural language, computer vision, and multi-modal data analytics. Proven track record of publishing in top-tier AI/ML conferences such as ICML, ICLR, NeurIPS, AAAI, IJCAI, AISTATS, SIGKDD, ACL, NAACL, CVPR, ICCV, ECCV, etc. Strong programming skills in AI/ML with hands-on experience in major AI platforms and tools. Experience in deploying AI frameworks like AI agents and autonomous systems is desirable. Education: B.Tech M.Tech (Dual), B.E., B.Tech, M.E.

Role - Lead AI Engineer Experience: 3+ years in AI/ML Location: Gurgaon, work from office About Tap Health: Tap Health is a deep-tech platform that is transforming chronic care management with AI and changing how you access health information. Powered by our proprietary Medical AI model, VaiD, Tap Health is designed to make healthcare accessible to millions. We are developing next-generation Digital Therapeutic products that redefine chronic illness management through AI-driven, hyper-personalized care. Our platform helps users manage conditions such as diabetes, hypertension, PCOS, pregnancy and asthma by delivering daily structured digital therapeutics, lifestyle interventions, personalized nutrition and exercise guidance and real-time monitoring, all without requiring human intervention. Leveraging AI and adaptive algorithms, Tap Health dynamically personalizes each users care journey, delivering enhanced insights, interventions, motivation, adherence and clinical outcomes at a fraction of traditional healthcare costs. Beyond Digital Therapeutics, the Tap Health platform also provides free primary illness diagnosis based on symptoms and instant health advice through a seamless, voice-first experience. www.tap.health Role Overview: Lead AI Engineer We are hiring a full-time Lead AI Engineer in Gurgaon to drive AI-driven healthcare innovations. The ideal candidate has 3+ years of AI/ML experience, 6+ months of GenAI production experience, and 1+ year of hands-on GenAI product development. You need to have a strong data science background and have expertise in GenAI, Agentic AI deployments, causal inference, and Bayesian modeling, with a strong foundation in LLMs and traditional models. You will be collaborating with the AI, Engineering, and Product teams to build scalable, consumer-focused healthcare solutions. As a Lead AI Engineer, you will be the go-to expertthe engineer others turn to when they hit roadblocks. You will mentor, collaborate, and enable high product velocity while fostering a culture of continuous learning and innovation. Skills & Experience The ideal candidate should have the following qualities: Strong understanding of fine-tuning, optimization, and neural architectures. Hands-on experience with Python, PyTorch, and FastAI frameworks. Experience running production workloads on one or more hyperscalers (AWS, GCP, Azure, Oracle, DigitalOcean, etc.). In-depth knowledge of LLMshow they work and their limitations. Ability to assess the advantages of fine-tuning, including dataset selection strategies. Understanding of Agentic AI frameworks, MCPs (Multi-Component Prompting), ACP (Adaptive Control Policies), and autonomous workflows. Familiarity with evaluation metrics for fine-tuned models and industry-specific public benchmarking standards in the healthcare domain. Knowledge of advanced statistical models, reinforcement learning, and Bayesian inference methods. Experience in Causal Inference and Experimentation Science to improve product and marketing outcomes. Proficiency in querying and analyzing diverse datasets from multiple sources to build custom ML and optimization models. Comfortable with code reviews and standard coding practices using Python, Git, Cursor, and CodeRabbit.,