3 Inferencing Jobs

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.,

ZS is a place where passion changes lives. As a management consulting and technology firm focused on improving life and how we live it, our most valuable asset is our people. Here you'll work side-by-side with a powerful collective of thinkers and experts shaping life-changing solutions for patients, caregivers, and consumers, worldwide. ZSers drive impact by bringing a client-first mentality to each and every engagement. We partner collaboratively with our clients to develop custom solutions and technology products that create value and deliver company results across critical areas of their business. Bring your curiosity for learning, bold ideas, courage, and passion to drive life-changing impact to ZS. At ZS, we honor the visible and invisible elements of our identities, personal experiences, and belief systemsthe ones that comprise us as individuals, shape who we are, and make us unique. We believe your personal interests, identities, and desire to learn are part of your success here. Learn more about our diversity, equity, and inclusion efforts and the networks ZS supports to assist our ZSers in cultivating community spaces, obtaining the resources they need to thrive, and sharing the messages they are passionate about. ZS's Beyond Healthcare Analytics (BHCA) Team is shaping one of the key growth vector areas for ZS, Beyond Healthcare engagement, comprising clients from industries like Quick service restaurants, Technology, Food & Beverage, Hospitality, Travel, Insurance, Consumer Products Goods & other such industries across North America, Europe & South East Asia region. The BHCA India team currently has a presence across New Delhi, Pune, and Bengaluru offices and is continuously expanding further at a great pace. The BHCA India team works with colleagues across clients and geographies to create and deliver real-world pragmatic solutions leveraging AI SaaS products & platforms, Generative AI applications, and other Advanced analytics solutions at scale. What You'll Do: - Build, Refine and Use ML Engineering platforms and components. - Scaling machine learning algorithms to work on massive datasets and strict SLAs. - Build and orchestrate model pipelines including feature engineering, inferencing, and continuous model training. - Implement ML Ops including model KPI measurements, tracking, model drift & model feedback loop. - Collaborate with client-facing teams to understand business context at a high level and contribute to technical requirement gathering. - Implement basic features aligning with technical requirements. - Write production-ready code that is easily testable, understood by other developers, and accounts for edge cases and errors. - Ensure the highest quality of deliverables by following architecture/design guidelines, coding best practices, periodic design/code reviews. - Write unit tests as well as higher-level tests to handle expected edge cases and errors gracefully, as well as happy paths. - Use bug tracking, code review, version control, and other tools to organize and deliver work. - Participate in scrum calls and agile ceremonies, and effectively communicate work progress, issues, and dependencies. - Consistently contribute to researching & evaluating the latest architecture patterns/technologies through rapid learning, conducting proof-of-concepts, and creating prototype solutions. What You'll Bring: - A master's or bachelor's degree in Computer Science or related field from a top university. - 4+ years hands-on experience in ML development. - Good understanding of the fundamentals of machine learning. - Strong programming expertise in Python, PySpark/Scala. - Expertise in crafting ML Models for high performance and scalability. - Experience in implementing feature engineering, inferencing pipelines, and real-time model predictions. - Experience in ML Ops to measure and track model performance, experience working with MLFlow. - Experience with Spark or other distributed computing frameworks. - Experience in ML platforms like Sage maker, Kubeflow. - Experience with pipeline orchestration tools such as Airflow. - Experience in deploying models to cloud services like AWS, Azure, GCP, Azure ML. - Expertise in SQL, SQL DB's. - Knowledgeable of core CS concepts such as common data structures and algorithms. - Collaborate well with teams with different backgrounds/expertise/functions. Perks & Benefits: ZS offers a comprehensive total rewards package including health and well-being, financial planning, annual leave, personal growth, and professional development. Our robust skills development programs, multiple career progression options, internal mobility paths, and collaborative culture empower you to thrive as an individual and global team member. We are committed to giving our employees a flexible and connected way of working. A flexible and connected ZS allows us to combine work from home and on-site presence at clients/ZS offices for the majority of our week. The magic of ZS culture and innovation thrives in both planned and spontaneous face-to-face connections. Travel: Travel is a requirement at ZS for client-facing ZSers; business needs of your project and client are the priority. While some projects may be local, all client-facing ZSers should be prepared to travel as needed. Travel provides opportunities to strengthen client relationships, gain diverse experiences, and enhance professional growth by working in different environments and cultures. Considering applying At ZS, we're building a diverse and inclusive company where people bring their passions to inspire life-changing impact and deliver better outcomes for all. We are most interested in finding the best candidate for the job and recognize the value that candidates with all backgrounds, including non-traditional ones, bring. If you are interested in joining us, we encourage you to apply even if you don't meet 100% of the requirements listed above. ZS is an equal opportunity employer and is committed to providing equal employment and advancement opportunities without regard to any class protected by applicable law. To Complete Your Application: Candidates must possess or be able to obtain work authorization for their intended country of employment. An online application, including a full set of transcripts (official or unofficial), is required to be considered. NO AGENCY CALLS, PLEASE.,

As an Applied AI/GenAI ML Director within the Asset and Wealth Management Technology Team at JPMorgan Chase, you will provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. You will leverage your deep expertise to consistently challenge the status quo, innovate for business impact, lead the strategic development behind new and existing products and technology portfolios, and remain at the forefront of industry trends, best practices, and technological advances. This role will focus on establishing and nurturing common capabilities, best practices, and reusable frameworks, creating a foundation for AI excellence that accelerates innovation and consistency across business functions. Your responsibilities will include establishing and promoting a library of common ML assets, including reusable ML models, features stores, data pipelines, and standardized templates. You will lead efforts to create shared tools and platforms that streamline the end-to-end ML lifecycle across the organization. Additionally, you will create curative solutions using GenAI workflows through advanced proficiency in large language models (LLMs) and related techniques, and gain experience with creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. You will advise on the strategy and development of multiple products, applications, and technologies, serving as a lead advisor on the technical feasibility and business need for AIML use cases. Furthermore, you will liaise with firm-wide AI ML stakeholders, translating highly complex technical issues, trends, and approaches to leadership to drive the firm's innovation and enable leaders to make strategic, well-informed decisions about technology advancements. You will also influence across business, product, and technology teams and successfully manage senior stakeholder relationships, championing the firm's culture of diversity, opportunity, inclusion, and respect. To be successful in this role, you must have formal training or certification on Machine Learning concepts and at least 10 years of applied experience, along with 5+ years of experience leading technologists to manage, anticipate, and solve complex technical items within your domain of expertise. An MS and/or PhD in Computer Science, Machine Learning, or a related field is required, as well as at least 10 years of experience in one of the programming languages like Python, Java, C/C++, etc., with intermediate Python skills being a must. You should have a solid understanding of using ML techniques, especially in Natural Language Processing (NLP) and Large Language Models (LLMs), hands-on experience with machine learning and deep learning methods, and the ability to work on system design from ideation through completion with limited supervision. Practical cloud-native experience such as AWS is necessary, along with good communication skills, a passion for detail and follow-through, and the ability to work effectively with engineers, product managers, and other ML practitioners. Preferred qualifications for this role include experience with Ray, MLFlow, and/or other distributed training frameworks, in-depth understanding of Embedding based Search/Ranking, Recommender systems, Graph techniques, and other advanced methodologies, advanced knowledge in Reinforcement Learning or Meta Learning, and a 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., is also desirable.,