Responsibilities:

• As a lead engineer in a fast-paced environment, you will play a pivotal role in shaping the future of Cisco’s AI strategies for the next decade and beyond.
• In this position, you will lead the development of AI/ML technologies for our products, revolutionizing our industry with groundbreaking AI solutions.
• Working closely with diverse teams, you will spearhead multi-functional engagements to architect, design, build, validate, deliver, and successfully deploy new products.
• You will collaborate closely with the AI/ML Product, Data Science Research teams, building AI/ML infrastructures and AI-powered networking solutions.
• Your role will involve effective communication across engineering teams, engaging both technologists and senior business executives.
• Working in partnership with developers, UX designers, and non-technical partners at Cisco, you will contribute to building the next generation of a unified experience platform.

Requirements & Skills:

• Bachelor’s degree or experience with 15+ years of Software Engineering principles and System Architecture or Master’s degree with 8+ years of product engineering experience
• 3+ years experience with AI/ML projects
• Experience in core ML/AI and deep learning technologies such as TensorFlow, PyTorch, Kubernetes, Huggin Face, Databricks, and LLM APIs
• Experience with cloud platforms (e.g., AWS, Azure, GCP)
• Experience using Containerization tools, such as Docker, with a deep understanding of ML/AI application development
• Experience programming in Go or Python languages
• Strong personal network across generative AI /ML industry & ecosystem
• Knowledge of industry trends and business needs to drive technology innovation and execution

The post Lead Engineer – AI / Machine Learning, Cisco appeared first on AI Jobs Latest.

Responsibilities:

• Design, build, and maintain end-to-end ML pipelines, including data processing, model training, evaluation, and deployment.
• Automate model deployment and lifecycle management across cloud and potential on-prem environments.
• Establish CI/CD workflows for ML models, ensuring reproducibility and traceability.
• Implement monitoring, logging, and alerting for model performance and drift detection.
• Optimize ML training and inference workloads for cost and performance efficiency.
• Collaborate with DevOps and engineering teams to integrate ML workloads with broader infrastructure.
• Define and implement MLOps best practices, including experiment tracking, versioning, and governance.
• Evaluate and recommend tools and frameworks for MLOps, considering both cloud and on-prem scenarios.

Requirements & Skills:

• 2-7+ years of experience in MLOps, DevOps, or related fields with a strong AI/ML focus.
• Hands-on experience with cloud platforms (GCP preferred) and container orchestration (Kubernetes, Docker).
• Proficiency in AI/ML pipeline frameworks (Kubeflow, MLflow, TFX, or similar).
• Strong knowledge of CI/CD tools (GitHub Actions, ArgoCD, or similar) for ML models.
• Experience with monitoring AI/ML models in production.
• Strong programming skills in Python, Bash, or Go.
• Familiarity with model-serving frameworks (TF Serving, Triton, BentoML) and decentralized / distributed computing (Ray, Spark).
• Experience in optimizing AI/ML workloads for GPUs and CPUs.
• Excellent problem-solving skills and ability to work in a fast-paced, evolving environment.

The post Machine Learning Operations Engineer, Revolut People appeared first on AI Jobs Latest.

The post Research Associate in the Division of Engineering, NYU appeared first on AI Jobs Latest.

Responsibilities:

• Work closely with and incorporate feedback from other specialists, tech-ops, and product managers
• Lead and engage in design reviews, architectural discussions, requirement definitions, and other technical activities in a diverse capacity
• Attend daily stand-up meetings, collaborate with your peers, prioritize features, and work with a sense of urgency to deliver value to your customers
• Finding quick ways to prototype and test possible solutions to large problems

Requirements & Skills:

• Bachelor’s degree in Computer Science or related fields.
• Interest in modern machine learning / deep learning systems
• Strong Computer Science fundamentals in algorithm design, complexity analysis, and performance
• Experience in programming with at least one modern programming language such as Java, C#, or Python, including object-oriented design
• Experience with applied machine learning models and large-scale ML systems

The post Machine Learning Engineer, Qualtrics appeared first on AI Jobs Latest.

Responsibilities:

• Serve as a subject matter expert on a wide range of ML techniques and optimizations.
• Provide in-depth knowledge of ML algorithms, frameworks, and techniques.
• Enhance ML workflows through advanced proficiency in large language models (LLMs) and related techniques.
• Conducting experiments using the latest ML technologies, analyzing results, tuning models
• Hands-on coding to bring the experimental results into production solutions by collaborating with the engineering team. Owning end-to-end code development in Python for both proof of concept/experimentation and production-ready solutions.
• Optimizing system accuracy and performance by identifying and resolving inefficiencies and bottlenecks. Collaborates with product and engineering teams to deliver tailored, science and technology-driven solutions.
• Integrate Generative AI within the ML Platform using state-of-the-art techniques.
• Drives decisions that influence the product design, application functionality, and technical operations and processes.

Requirements & Skills:

• MS and/or PhD in Computer Science, Machine Learning, or a related field, with at least 5 years of applied machine learning experience.
• At least 5 years experience in one of the programming languages like Python, Java, C/C++, etc. Intermediate Python is a must.
• At least 5 years’ experience in applying data science, ML techniques to solve business problems.
• Solid background in Natural Language Processing (NLP) and Large Language Models (LLMs)
• Hands-on experience with machine learning and deep learning methods.
• Deep understanding and expertise in deep learning frameworks such as PyTorch or TensorFlow.
• Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search).
• Ability to work on tasks and projects through to completion with limited supervision.
• Passion for detail and follow-through. Excellent communication skills and team player
• Demonstrated leadership in working effectively with engineers, product managers, and other ML practitioners.
• Experience with Ray, MLFlow, and/or other distributed training frameworks.
• In-depth understanding of Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies.
• Advanced knowledge in Reinforcement Learning or Meta-Learning.
• Deep understanding of Large Language Model (LLM) techniques, including Agents, Planning, Reasoning, and other related methods.
• Experience with building and deploying ML models on cloud platforms such as AWS and AWS tools like Sagemaker, EKS, etc.

The post AIML Lead – GenAI & LLM, JPMorganChase appeared first on AI Jobs Latest.

Responsibilities:

• Designing and supporting machine learning applications for cutting-edge ICs and SoCs within the Machine Learning Center of Excellence (ML CoE) team.
• Identifying opportunities in VLSI design workflows and proposing solutions using generative AI and machine learning techniques to improve VLSI design quality and designer productivity.
• Designing and implementing highly efficient data structures and algorithms.
• Committing to deliver top-quality production software that exceeds customer expectations.
• Collaborating with cross-functional teams to innovate and develop new features for AI-driven EDA applications.

Requirements & Skills:

• Driving innovation in AI-driven EDA applications to help customers design complex chips.
• Contributing to the development of the industry’s first AI-driven implementation platform, DSO.ai.
• Prototyping, designing, and developing new features for AI-driven EDA tools.
• Enhancing the performance and quality of Synopsys’s AI-driven EDA tools.
• Collaborating with global teams to push the boundaries of AI and EDA integration.
• Strong CS fundamentals (data structures, algorithms, object-oriented design, computer architecture, operating systems, distributed systems).
• Experience with developing machine learning projects/applications.
• Familiarity with VLSI digital design and implementation flows like synthesis, place, and route.
• BSc/MSc or PhD degree in Electrical Engineering, Computer Science, or related discipline.
• 3-5 years of experience in a similar role.
• Working knowledge in developing and maintaining complex Python/C/C++ applications in a Unix/Linux environment.
• Knowledge of machine learning, design of algorithms with efficient data structures, neural networks, and pattern matching.
• Knowledge of EDA design tool implementation and signoff flows.

The post Machine Learning Software Engineer, Synopsys appeared first on AI Jobs Latest.