11 Federated Learning Jobs

As a Global Product Lead at MiQ, a global programmatic media partner, you will play a crucial role in leading and expanding a unified Data Management and LLMOps framework. Your responsibilities will include: - Leading and expanding a unified Data Management and LLMOps framework across various functions such as engineering, analytics, data science, and ad operations. - Architecting and managing automated data pipelines for onboarding, cleansing, and processing structured and unstructured data using advanced AI/agentic automation. - Overseeing the adoption and execution of Agentic AI in data workflows, defining and scaling LLMOps best practices, and ensuring seamless orchestration of AI models. - Driving the implementation and expansion of privacy-enhancing technologies like data clean rooms, federated learning, and privacy-preserving data matching. - Embedding robust data governance policies across the data and AI lifecycle, including lineage, minimization, quality controls, regulatory compliance, and AI-ethics frameworks. - Collaborating with various teams to identify and deliver on emerging data and AI opportunities, and championing MiQ's data as a product culture globally. - Providing executive reporting on goals, metrics, and progress related to AI-driven data management, cost oversight, and vendor engagement. - Fostering innovation while prioritizing commercial value, evaluating agentic or LLM-powered solutions for feasibility, risk, and business alignment. - Leading, mentoring, and inspiring a team of next-generation product managers, engineers, and applied AI specialists. - Being a recognized industry thought leader on Data Management, Agentic AI, LLMOps, and Adtech best practices internally and externally. What impact will you create - Vision for the future of AI-powered, privacy-first, and agentic data management in Adtech. - Track record of rolling out LLMOps frameworks and proven ability to balance innovation with commercial practicality. - Industry presence: Bringing new ideas from AI research, open source, and the privacy tech landscape into business practice. Your stakeholders will mainly include analysts, data scientists, and product teams at MiQ. What You'll Bring: - 10+ years of experience in data management and product leadership with expertise in agentic AI, LLMOps, or advanced AI/ML productization. - Direct experience in delivering enterprise-grade data management ecosystems and AI/LLM-powered solutions, preferably in Adtech or MarTech. - Deep familiarity with data governance for AI, including ethical frameworks, responsible innovation, synthetic data, and regulatory compliance. - Extensive hands-on experience with contemporary data and ML stack and integrating large-scale LLM pipelines. - Demonstrated ability to coach and scale high-performing teams in dynamic product settings. - Strong operational leadership and collaboration skills at C-level and in cross-functional global environments. - Up-to-date knowledge of relevant Adtech and MarTech topics. MiQ values passion, determination, agility, unity, and courage, and fosters a welcoming culture committed to diversity, equity, and inclusion. In return, you can expect a hybrid work environment, new hire orientation and training, internal and global mobility opportunities, competitive healthcare benefits, bonus and performance incentives, generous annual PTO, and employee resource groups supporting diversity and inclusion initiatives. If you have a passion for this role, apply today and be part of our team at MiQ, an Equal Opportunity Employer.,

You are a Machine Learning & Generative AI Engineer responsible for designing, building, and deploying advanced ML and GenAI solutions. This role presents an exciting opportunity to work on cutting-edge AI systems, such as LLM fine-tuning, Transformer architectures, and RAG pipelines, while also contributing to traditional ML model development for decision-making and automation. With a minimum of 3 years of experience in Machine Learning, Deep Learning, and AI model development, you are expected to demonstrate a strong proficiency in Python, PyTorch, TensorFlow, Scikit-Learn, and MLflow. Your expertise should encompass Transformer architectures (such as BERT, GPT, T5, LLaMA, Falcon) and attention mechanisms. Additionally, experience with Generative AI, including LLM fine-tuning, instruction tuning, and prompt optimization is crucial. You should be familiar with RAG (Retrieval-Augmented Generation) embeddings, vector databases (FAISS, Pinecone, Weaviate, Chroma), and retrieval workflows. A solid foundation in statistics, probability, and optimization techniques is essential for this role. You should have experience working with cloud ML platforms like Azure ML / Azure OpenAI, AWS SageMaker / Bedrock, or GCP Vertex AI. Familiarity with Big Data & Data Engineering tools like Spark, Hadoop, Databricks, and SQL/NoSQL databases is required. Proficiency in CI/CD, MLOps, and automation pipelines (such as Airflow, Kubeflow, MLflow) is expected, along with hands-on experience with Docker and Kubernetes for scalable ML/LLM deployment. It would be advantageous if you have experience in NLP & Computer Vision areas, including Transformers, BERT/GPT models, YOLO, and OpenCV. Exposure to vector search & embeddings for enterprise-scale GenAI solutions, multimodal AI, Edge AI / federated learning, RLHF (Reinforcement Learning with Human Feedback) for LLMs, real-time ML applications, and low-latency model serving is considered a plus. Your responsibilities will include designing, building, and deploying end-to-end ML pipelines covering data preprocessing, feature engineering, model training, and deployment. You will develop and optimize LLM-based solutions for enterprise use cases, leveraging Transformer architectures. Implementing RAG pipelines using embeddings and vector databases to integrate domain-specific knowledge into LLMs will also be part of your role. Fine-tuning LLMs on custom datasets for domain-specific tasks and ensuring scalable deployment of ML & LLM models on cloud environments are critical responsibilities. Collaborating with cross-functional teams comprising data scientists, domain experts, and software engineers to deliver AI-driven business impact is expected from you.,

As an experienced AI/ML Engineer, you will be an integral part of our team working on Mizzle Mate, an AI-driven DevOps automation platform. Your primary responsibility will be to design, develop, and deploy AI/ML models for predictive analytics, anomaly detection, and intelligent automation within Mizzle Mate. You will also work on developing NLP-based chatbots, AI-driven observability, and automated monitoring solutions to enhance the platform's capabilities. Utilizing your expertise in artificial intelligence, machine learning, and data science, you will collaborate with DevOps, cloud engineers, and software developers to integrate AI solutions seamlessly into Mizzle's cloud ecosystem. Furthermore, you will research and implement cutting-edge AI/ML techniques such as deep learning, reinforcement learning, and generative AI to keep our platform at the forefront of innovation. Your role will also involve optimizing ML models for performance, scalability, and real-time inference, as well as implementing AI-based recommendations for infrastructure optimization, security compliance, and incident resolution. Additionally, you will be responsible for developing APIs and AI microservices to integrate with Mizzle's IAM, compute, storage, and GPU services while ensuring data security, compliance, and governance. To be successful in this position, you should hold a Bachelors/Masters degree in Computer Science, AI, Data Science, or related fields, along with a minimum of 3 years of experience in AI/ML development, preferably in cloud, DevOps, or security domains. Strong programming skills in Python, TensorFlow, PyTorch, or Scikit-learn are essential, as well as experience with NLP, LLMs, and generative AI frameworks. Familiarity with MLOps, model deployment, CI/CD pipelines, AWS/GCP/Azure AI services, Kubernetes, big data, distributed computing, and real-time analytics is also required. Candidates with expertise in cybersecurity, OWASP standards, and AI-driven threat detection will be preferred. Knowledge of vector databases, embedding models, and retrieval-augmented generation (RAG) will be considered a plus. Your problem-solving skills and ability to thrive in a fast-paced environment will be key to your success in this role. Preferred qualifications include experience in DevOps AI, AIOps, self-healing infrastructure, blockchain-based AI solutions, federated learning, and privacy-preserving AI techniques.,

As an AI Model Developer in the manufacturing sector, you will be responsible for developing, architecting, and designing AI models that focus on predictive maintenance, quality control, and process optimization to improve manufacturing efficiency. Your role will involve analyzing manufacturing data to identify patterns, inefficiencies, and areas for process enhancements. You will design and implement machine learning, deep learning, and vision AI models for anomaly detection, forecasting, and optimizing supply chains. Furthermore, you will be required to integrate these AI models into Manufacturing Execution Systems (MES), Internet of Things (IoT) frameworks, and SAP/ERP systems to facilitate real-time operational insights. Collaboration with cross-functional teams to translate manufacturing challenges into data-driven AI solutions will be a key aspect of your responsibilities. Additionally, you will explore and apply cutting-edge technologies such as Generative AI, Edge Computing, and Digital Twin to drive innovation in the manufacturing domain. To excel in this role, you should possess at least 8 years of experience, with a minimum of 2 years in manufacturing or industrial domains. A Bachelor's degree in Engineering (Mechanical/Electrical/Computer) and a Master's degree in business, Computer Science, Data Science, or Artificial Intelligence are essential qualifications. Proficiency in Python, SQL, and ML frameworks like TensorFlow and PyTorch is required. Knowledge of manufacturing systems such as MES, SCADA, or ERP, along with experience in cloud platforms like Azure, AWS, or GCP, will be advantageous. Familiarity with emerging AI trends like Explainable AI, Federated Learning, and Edge AI is desirable. Strong communication and interpersonal skills, effective time management, and the ability to meet project deadlines are essential for success in this role.,

As an AI Engineer at ManMukt, a pioneering organization dedicated to transforming mental healthcare through innovative AI solutions, you will play a crucial role in developing and implementing AI models specific to mental health applications. Your expertise will contribute to creating accessible, personalized, and effective digital health tools that aim to make quality mental healthcare available to everyone, everywhere. Your responsibilities will include designing, developing, and deploying sophisticated machine learning and deep learning models tailored for mental health, as well as leading the development of natural language processing systems to understand emotional and psychological contexts. You will also be involved in creating predictive models for early detection and intervention of mental health concerns, collaborating with clinical experts, optimizing algorithms, and implementing data privacy and security protocols for sensitive health information. Furthermore, you will lead technical discussions with stakeholders, mentor junior AI engineers and data scientists, stay updated with emerging research in AI applications for mental health, and contribute to the development of ethical frameworks for AI in healthcare settings. To qualify for this role, you should hold a Bachelor's degree in Computer Science, AI, Machine Learning, or a related field, with 5-6 years of professional experience in AI/ML engineering roles, including at least 3 years specifically in mental health or healthcare technology. Proficiency in machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn, expertise in NLP techniques and emotional sentiment analysis, as well as strong communication skills to translate technical concepts to non-technical stakeholders are essential. Preferred qualifications include experience with multimodal AI systems, knowledge of digital phenotyping, familiarity with privacy-preserving ML techniques, experience with EHR systems, and a publication record in mental health technology or related fields. At ManMukt, you will have the opportunity to work on meaningful AI applications that directly improve mental healthcare, along with competitive salary and benefits, flexible remote work options, continuous learning opportunities, and a collaborative, innovative team environment. Join us in shaping the future of AI applications in mental healthcare. To apply for this position, please submit your resume, a cover letter emphasizing your relevant experience in mental health AI, and any relevant portfolio items or publications to info@manmukt.in with the subject line "AI Engineer - Mental Health". ManMukt is an equal opportunity employer dedicated to fostering a diverse and inclusive team, welcoming applications from candidates of all backgrounds, particularly those underrepresented in technology and healthcare.,

If you are a smart, self-motivated Machine Learning Scientist with a passion for advancing the field of Generative AI, an excellent opportunity awaits you. EXL, a rapidly expanding global digital data-led AI transformation solutions company, is seeking candidates with deep expertise in developing and fine-tuning Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), agentic solutions, and knowledge graph technologies to drive innovative solutions in Generative AI. You will have the chance to be at the forefront of pioneering advancements in AI, working alongside bright minds in an exciting R&D environment to build cutting-edge capabilities that redefine the future of artificial intelligence. In this role, you will develop initiatives in the Generative AI domain, focusing on cutting-edge technologies like LLMs, RAG, and autonomous agents. You will design and implement advanced workflows for integrating LLMs into real-world applications across domains such as Finance, Insurance, and Healthcare. Additionally, you will drive the development of retrieval-augmented systems by combining LLMs with document retrieval, clustering, and search techniques. Keeping abreast of AI advancements is essential, as you will be required to read, adapt, and implement cutting-edge research to solve real-world challenges. Documenting research findings, methodologies, and implementations for internal and external stakeholders will also be part of your responsibilities. Qualifications: - Experience: 2-5 years in AI/ML research and development, with at least 1-2 years focusing on Generative AI, LLMs, or related fields. - Education: Masters or PhD in Computer Science, AI, or a related field from a top-tier institution is highly preferred. Required Skills: - Core Expertise: Proven experience with Large Language Models (e.g., GPT-4, BERT, LLaMA, PaLM) and fine-tuning them for domain-specific applications. In-depth knowledge of Retrieval-Augmented Generation workflows and hands-on experience with autonomous agents. - Tools & Frameworks: Proficiency in deep learning frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. Experience with distributed training and optimization on GPUs and TPUs. Familiarity with cloud ecosystems (AWS, Azure, Google Cloud) practices for scalable deployment. - Research & Development: Ability to read and adapt cutting-edge research papers for applied solutions in LLMs and knowledge graphs. Expertise in domain adaptation, few-shot learning, and zero-shot reasoning. Strong understanding of generative models and their integration with LLMs. - Problem Solving: Demonstrated ability to address challenges in unstructured data processing, including NLP and multimodal scenarios. Experience with document retrieval, clustering, and unsupervised learning techniques. Preferred Skills: - Experience with LLM fine-tuning and building Agentic systems for domain LLMs. Experience with reinforcement learning and fine-tuning via RLHF. Knowledge of large-scale optimization methods and efficient model compression techniques. Strong collaboration and communication skills, with a proven ability to lead teams. Experience with MoE based architecture and knowledge of federated learning.,

As an Assistant Vice President Generative AI Systems Architect, you will leverage your 12+ years of experience to architect and design end-to-end systems for production-grade Generative AI applications. This includes creating systems for LLM-based chatbots, copilots, and content generation tools. Your responsibilities will involve defining system architecture for data ingestion, model training/fine-tuning, inferencing, and deployment pipelines. It is essential to establish architectural tenets such as modularity, scalability, reliability, observability, and maintainability. Collaboration plays a crucial role in this role, as you will work closely with data scientists, ML engineers, platform engineers, and product managers to ensure that the architecture aligns with both business objectives and AI goals. Your tasks will include choosing and integrating foundation models, evaluating solutions based on various architecture patterns, and designing secure and compliant architectures for enterprise settings, focusing on data governance, auditability, and access control. Additionally, you will lead system design reviews, define non-functional requirements (NFRs) like latency, availability, throughput, and cost, and collaborate with MLOps teams to establish CI/CD processes for model and system updates. Your contribution to creating reference architectures, design templates, and reusable components will be valuable in driving efficiency and consistency across projects. To excel in this role, it is important to stay updated with the latest advancements in GenAI, system design patterns, and AI platform tooling. Your role as an Assistant Vice President Generative AI Systems Architect will be dynamic and impactful, contributing significantly to the advancement and implementation of cutting-edge AI technologies.,

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

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra - India). The ideal candidate should have 12-15+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. Top 3 Daily Tasks: Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed "invisible intelligence" within secure wearable systems. Must have 12-15+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Must have: Programming languages: Python C/C++ Java Kotlin JavaScript/Node.js Swift Objective-C CUDA Shell scripting Expert in: TensorFlow PyTorch ONNX HuggingFace model optimization with TensorRT TFLite Deep experience with: LLMs RAG pipelines vector DBs (FAISS, Milvus) Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops Strong in privacy-preserving AI (federated learning, differential privacy) Secure real-time comms (WebRTC, SIP, RTP) Nice to have: Experience with MCP or similar protocol frameworks Background in wearables/XR or smart glass AI platforms Expertise in platform security architectures (sandboxing, auditability) Show more Show less

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra India). The ideal candidate should have 1215+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. 1. Top 3 Daily Tasks: - Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. - Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. - Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed invisible intelligence within secure wearable systems. 2. Must have: - Must have 1215+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Programming languages: Python C/C++ Java Kotlin JavaScript/Node.js Swift Objective-C CUDA Shell scripting - Expert in: TensorFlow PyTorch ONNX HuggingFace model optimization with TensorRT TFLite - Deep experience with: LLMs RAG pipelines vector DBs (FAISS, Milvus) - Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops - Strong in privacy-preserving AI (federated learning, differential privacy) - Secure real-time comms (WebRTC, SIP, RTP) 3. Nice to have: - Experience with MCP or similar protocol frameworks - Background in wearables/XR or smart glass AI platforms - Expertise in platform security architectures (sandboxing, auditability) Show more Show less

We are looking for a Director of Engineering (AI Systems & Secure Platforms) to join our client&aposs Core Engineering team at Thane (Maharashtra India). The ideal candidate should have 1215+ years of experience in architecting and deploying AI systems at scale, with deep expertise in agentic AI workflows, LLMs, RAG, Computer Vision, and secure mobile/wearable platforms. Top 3 Daily Tasks: ? Architect, optimize, and deploy LLMs, RAG pipelines, and Computer Vision models for smart glasses and other edge devices. ? Design and orchestrate agentic AI workflowsenabling autonomous agents with planning, tool usage, error handling, and closed feedback loops. ? Collaborate across AI, Firmware, Security, Mobile, Product, and Design teams to embed invisible intelligence within secure wearable systems. Must have 1215+ years of experience in Applied AI, Deep Learning, Edge AI deployment, Secure Mobile Systems, and Agentic AI Architecture. Must have: -Programming languages: Python, C/C++, Java (Android), Kotlin, JavaScript/Node.js, Swift, Objective-C, CUDA, Shell scripting -Expert in TensorFlow, PyTorch, ONNX, HuggingFace; model optimization with TensorRT, TFLite -Deep experience with LLMs, RAG pipelines, vector DBs (FAISS, Milvus) -Proficient in agentic AI workflowsmulti-agent orchestration, planning, feedback loops -Strong in privacy-preserving AI (federated learning, differential privacy) -Secure real-time comms (WebRTC, SIP, RTP) Nice to have: -Experience with MCP or similar protocol frameworks -Background in wearables/XR or smart glass AI platforms -Expertise in platform security architectures (sandboxing, auditability) Industry Technology, Information and Internet Employment Type Full-time Show more Show less