7 Inferencing Jobs

As an Applied AI/GenAI ML Director at JPMorgan Chase, you will play a pivotal role in collaborating with agile teams to enhance, create, and deliver cutting-edge technology products in a secure and scalable manner. Your expertise will be instrumental in challenging the norm, driving innovation, and leading the strategic development of new products and technology portfolios. By staying updated on industry trends and best practices, you will establish common capabilities and frameworks for AI excellence across the organization. - Establish and promote a library of common ML assets, including reusable models, features stores, data pipelines, and standardized templates. - Lead the creation of shared tools and platforms to streamline the end-to-end ML lifecycle. - Develop curative solutions using GenAI workflows and advanced proficiency in Large Language Models (LLMs). - Gain experience in creating a Generative AI evaluation and feedback loop for GenAI/ML pipelines. - Provide guidance on the strategy and development of products, applications, and technologies. - Act as a lead advisor on the technical feasibility and business need for AIML use cases. - Collaborate with AI ML stakeholders across the organization. - Translate complex technical issues for leadership to drive innovation and informed decision-making. - Influence business, product, and technology teams while managing senior stakeholder relationships. - Champion a culture of diversity, opportunity, inclusion, and respect within the firm. Qualifications and Skills Required: - Formal training or certification in Machine Learning concepts with over 10 years of applied experience in programming languages like Python, Java, or C/C++. - MS and/or PhD in Computer Science, Machine Learning, or related field. - Strong understanding of ML techniques, especially in NLP and LLMs. - Experience in AI implementation in software development and legacy code transformation. - Familiarity with agentic workflows and frameworks like LangChain and LangGraph. - Proficiency in deep learning frameworks such as PyTorch or TensorFlow. - Knowledge in advanced ML areas like GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG. - Ability to work on system design from ideation to completion with limited supervision. - Excellent communication and teamwork skills, with a passion for detail and follow-through. - Demonstrated leadership in collaborating effectively with engineers, product managers, and ML practitioners. - Practical experience in cloud-native environments like AWS. Preferred Qualifications: - Experience with distributed training frameworks like Ray and MLFlow. - Understanding of advanced methodologies such as Embedding-based Search/Ranking, Recommender systems, and Graph techniques. - Proficiency in Reinforcement Learning or Meta Learning. - Deep knowledge of LLM techniques, including Agents, Planning, and Reasoning. - Experience in building and deploying ML models on AWS platforms using tools like Sagemaker and EKS.,

As a Software Engineer III at JPMorganChase within the AI/ML & Data Platform team, you will play a critical role in designing and delivering market-leading technology products. Here's a summary of what you can expect in this role: **Role Overview:** You will be a seasoned member of an agile team, responsible for executing software solutions, design, development, and technical troubleshooting. Your role involves creating secure and high-quality production code, maintaining algorithms, and producing architecture and design artifacts for complex applications. Additionally, you will gather, analyze, synthesize, and develop visualizations and reporting from large data sets to drive continuous improvement of software applications and systems. **Key Responsibilities:** - Execute software solutions with innovative approaches - Create secure and high-quality production code - Produce architecture and design artifacts for complex applications - Gather, analyze, synthesize, and develop visualizations and reporting from large data sets - Identify hidden problems and patterns in data for system improvements - Contribute to software engineering communities of practice and events - Foster a team culture of diversity, opportunity, inclusion, and respect **Qualifications Required:** - Formal training or certification in AI/ML concepts with 3+ years of applied experience - Hands-on experience in programming languages, particularly Python - Ability to apply data science and machine learning techniques to address business challenges - Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) - Expertise in deep learning frameworks such as PyTorch or TensorFlow - Strong communication skills and demonstrated leadership in collaborating effectively with team members Please note that the job description does not include any additional details about the company.,

As a Software Engineer III at JPMorganChase within the AI/ML & Data Platform team, you will play a crucial role in designing and delivering trusted technology products in a secure, stable, and scalable manner. Your responsibilities will involve executing software solutions, troubleshooting technical issues, and creating secure production code that aligns with design constraints. Additionally, you will be involved in analyzing and synthesizing data sets to drive continuous improvement in software applications. **Key Responsibilities:** - Execute software solutions, design, development, and technical troubleshooting with innovative approaches - Create secure and high-quality production code, maintaining algorithms for synchronous operation - Produce architecture and design artifacts for complex applications, ensuring design constraints are met - Analyze and synthesize data sets to develop visualizations and reporting for software applications enhancement - Identify hidden problems and patterns in data to drive improvements in coding hygiene and system architecture - Contribute to software engineering communities of practice and events exploring new technologies - Foster a team culture of diversity, opportunity, inclusion, and respect **Qualifications Required:** - Formal training or certification in AI/ML concepts with a minimum of 3 years of applied experience - Hands-on experience in programming languages, especially Python - Ability to apply data science and machine learning techniques to solve business challenges - Strong background in Natural Language Processing (NLP) and Large Language Models (LLMs) - Expertise in deep learning frameworks like PyTorch or TensorFlow, and advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, and RAG (Similarity Search) - Capable of completing tasks independently with minimal supervision, demonstrating attention to detail and follow-through - Excellent communication skills, team player, and proven leadership in collaborating with engineers, product managers, and ML practitioners *Note: Preferred qualifications, capabilities, and skills are not provided in the job description.*,

We have an opportunity to impact your career and provide an adventure where you can push the limits of what's possible. As a Lead Software Engineer at JPMorganChase within the Employee Platforms team, you serve as a seasoned member of an Incubation and Research team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm's business objectives. This role requires a unique ability to apply state-of-the-art technical skills, work with ambiguity, and deliver projects to completion. You will be instrumental in developing innovative solutions, finding market fit, and delivering products that resonate with our users. As a hands-on engineer, you will bring in cutting-edge technologies, including Generative AI and ML. Job responsibilities Execute software solutions, design, development, and technical troubleshooting with the ability to think beyond routine or conventional approaches to build solutions or break down technical problems. Embrace ambiguity and lead the development of innovative solutions without a predefined roadmap. Implement the Build-Measure-Lean loop by rapidly prototyping, testing, and iterating on engineering solutions. Analyze user feedback and technical challenges to refine product offerings and ensure alignment with user needs. Create secure and high-quality production code and maintain algorithms that run synchronously with appropriate systems. Produce architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development. Gather, analyze, synthesize, and develop visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems. Proactively identify hidden problems and patterns in data and use these insights to drive improvements to coding hygiene and system architecture. Contribute to software engineering communities of practice and events that explore new and emerging technologies. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and 5+ years applied experience Hands-on practical experience in Python, SQL, advanced GenAI technologies like multimodality (Voice & Images), Agentic AI and ML technologies Highly proficient in coding in one or more languages such as Python, SQL, Java and R programming languages Experience with one or more platform tech stacks such as AWS, Docker, Kubernetes, Data bricks and CI/CD pipelines. Solid understanding of using ML techniques specially in Natural Language Processing (NLP), Knowledge Graph and Large Language Models (LLMs) Experience in advanced applied ML areas such as GPU optimization, finetuning, embedding models, inferencing, prompt engineering, evaluation, RAG (Similarity Search) Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages Overall knowledge of the Software Development Life Cycle Solid understanding of agile methodologies such as CI/CD, application resiliency, and security Preferred qualifications, capabilities, and skills Proficiency in optimizing and tuning AI models to ensure efficient, scalable solutions, with experience in building and deploying ML models on cloud platforms such as AWS and using tools like Sagemaker and EKS. Knowledge of data engineering practices to support AI model training and deployment, along with a strong understanding of machine learning algorithms and techniques-including supervised, unsupervised, and reinforcement learning-and hands-on experience with libraries such as TensorFlow, PyTorch, Scikit-learn, and Keras. Skills in collaborating with cross-functional teams to integrate generative AI solutions into broader business processes and applications, leveraging advanced LLM techniques such as Agents, Planning, and Reasoning. In-depth understanding of embedding-based search/ranking, recommender systems, graph techniques, and other advanced methodologies to enhance AI solution capabilities.

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.,