8 jobs found

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile 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. You will work on challenging Cloud-native data, backend engineering and AIML engineering, helping us industrialize AI/ML models at production scale. This role is a technical hands on engineering role. Experience with data science/ML modeling is advantageous but not essential to this role. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high-quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces a passion for learning, problem-solving, creative thinking and a can-do attitude. Required qualifications, capabilities, and skills Formal training or certification onsoftware engineeringconcepts and proficient applied experience Hands on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages- Python 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 Proven track record in system design, architecting and developing microservices, distributed systems and data-intensive applications Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies Practical experience developing Production scale Cloud-native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds Preferred qualifications, capabilities, and skills Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector Experience working on recommendation systems, LLM applications or other AI/ML systems Practical experience with Kubernetes, EKS, Docker, MLOps Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases Prior experience collaborating with data scientists

JPMorgan Chase & Co. invites a Machine Learning Lead Software Engineer to join the RCORT team. You will design and deliver trusted AI/ML technology products with secure, scalable architecture, leading a team across multiple domains and collaborating with product, data science, and engineering stakeholders. You will build production grade Agentic AI services, end to end AIML pipelines, and leverage Python, LLMs, and ML Ops to achieve business objectives.

At GSK, we see a world where advanced applications of Machine Learning and AI enable us to develop transformational medicines that drive better outcomes for patients at reduced cost and with fewer side effects. AI will also play a role in how we diagnose and use medicines to enable everyone to do more, feel better, and live longer. It is an ambitious vision that will require the development of products at the cutting edge of Machine Learning and AI. About the Role To strengthen our AI for Science (AI4S) team, we are looking for AI/ML Engineers with a track record in developing and validating machine learning models for real world scientific problems. You will drive the development of AI models and agentic systems-researching, designing, implementing, and delivering solutions across a range of scientific tasks, leveraging high performance computing and the biomedical data sources available at GSK. Team Culture The AI4S team is built on the principles of ownership, accountability, continuous development, and collaboration. We hire for the long term and are motivated to make this a great place to work. Our leaders will be committed to your career and development from day one. We strongly encourage applications from people with diverse and underrepresented backgrounds and perspectives. In this role you will Design and implement AI/ML driven solutions throughout the entire model development life cycle. Research and develop state of the art machine learning models and agentic systems to solve a variety of scientific tasks. Deliver robust, tested, and high performance code in an agile environment. Liaise with experts in biology, medicine and experimentation to ensure optimal data collection and processing for machine learning models. Qualifications & Skills Bachelor's, Master's or Doctorate degree in a quantitative or engineering discipline (computer science, computational biology, bioinformatics, engineering, among others); OR equivalent work experience delivering state of the art AI/ML solutions. Experience with at least one major deep learning framework (PyTorch, JAX, TensorFlow). Familiarity with machine learning literature and state of the art approaches. Experience developing and delivering robust software solutions, including demonstrated advanced programming expertise in Python. Experience in software engineering and machine learning best practices, including version control, continuous integration (CI) and continuous development (CD), containerization, and shell scripting. Fluency in English. Preferred Qualifications Experience in design, development and deployment of commercial AI/ML software. Experience with Large Language Models (LLMs) and Agentic AI (e.g., tool use, multi agent orchestration, deployment and evaluation). Contributions to relevant open source projects. Relevant scientific publications in AI/ML (e.g., NeurIPS, ICML, ICLR, AAAI), computational biology or bioinformatics venues. Knowledge of or interest in disease biology, molecular biology and medicine. Experience working with biomedical data (e.g., genomics, transcriptomics, proteomics, electronic health records, clinical images). If you are based in Cambridge, MA; Waltham, MA; Rockville, MD; or San Francisco, CA, the annual base salary for new hires in this position ranges $160,050 to $266,750. The US salary ranges take into account a number of factors including work location within the US market, the candidate's skills, experience, education level and the market rate for the role. In addition, this position offers an annual bonus and eligibility to participate in our share based long term incentive program which is dependent on the level of the role. Available benefits include health care and other insurance benefits (for employee and family), retirement benefits, paid holidays, vacation, paid caregiver/parental and medical leave. GSK is an Equal Opportunity Employer. This ensures that all qualified applicants will receive equal consideration for employment without regard to race, color, religion, sex (including pregnancy, gender identity, and sexual orientation), parental status, national origin, age, disability, genetic information (including family medical history), military service or any basis prohibited under federal, state or local law.

Job Overview We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile 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. You will work on challenging Cloud native data, backend engineering, and AIML engineering, helping us industrialize AI/ML models at production scale. This role is a technical hands on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role. Job Responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Drives adoption and governance of approved AI assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI assisted code review/refactoring, test acceleration, release readiness, incident/root cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI assisted development and automation capabilities, to improve the value realized by automation at scale. Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces a passion for learning, problem solving, creative thinking and a can do attitude. Required Qualifications, Capabilities, and Skills Formal training or certification on software engineering concepts and proficient applied experience Hands on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages - Python 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 Proven track record in system design, architecting and developing microservices, distributed systems and data intensive applications Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies Practical experience developing production scale Cloud native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Demonstrated experience leading effective use of enterprise authorized AI assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls. Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds Preferred Qualifications, Capabilities, and Skills Experience with data, AWS and AIML engineering in commercial settings, preferably in the financial sector Experience working on recommendation systems, LLM applications or other AI/ML systems Practical experience with Kubernetes, EKS, Docker, MLOps Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases Prior experience collaborating with data scientists Equal Employment Opportunity We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs.

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Senior Lead Software Engineer at JPMorgan Chase within the Commercial & Investment Bank's Markets Research Technology team, you serve as a seasoned member of an agile 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. You will work on challenging Cloud native data, backend engineering and AIML engineering, helping us industrialize AI/ML models at Production scale. This role is a technical hands on Engineering role. Experience with data science/ML modeling is advantageous but not essential to this role. Job responsibilities Executes software solutions, design, development, and technical troubleshooting with ability to think beyond routine or conventional approaches to build solutions or break down technical problems Creates secure and high quality production code and maintains algorithms that run synchronously with appropriate systems Produces architecture and design artifacts for complex applications while being accountable for ensuring design constraints are met by software code development Builds engineering stack required for Data and AIML products, including data engineering, backend engineering, Cloud infra DevOps and MLOps Designs and implements data engineering solutions, leveraging modern big data technologies Drives adoption and governance of approved AI assisted engineering practices across teams to improve code quality, delivery speed, and operational outcomes (e.g., AI assisted code review/refactoring, test acceleration, release readiness, incident/root cause analysis), while establishing measurable validation standards (secure coding, peer review, automated testing) and promoting reuse of proven patterns and automation within the SDLC/TLM toolchain. Applies knowledge of tools within the Software Development Life Cycle toolchain, including approved AI assisted development and automation capabilities, to improve the value realized by automation at scale. Contributes to software engineering communities of practice and events that explore new and emerging technologies Embraces a passion for learning, problem solving, creative thinking and a can do attitude. Required qualifications, capabilities, and skills Formal training or certification onsoftware engineeringconcepts and proficient applied experience Hands on practical experience in system design, application development, testing, and operational stability Proficient in coding in one or more languages- Python 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 Proven track record in system design, architecting and developing microservices, distributed systems and data intensive applications Experience with Cloud services, Infrastructure as Code, containerized application development, big data and modern data engineering technologies Practical experience developing Production scale Cloud native data engineering solutions in commercial environments Familiarity with Cloud Data engineering services (e.g., ETL, Glue, S3, Athena) and MLOps stack Demonstrated experience leading effective use of enterprise authorized AI assisted software development tools within the work environment (e.g., for coding, code review, test acceleration, troubleshooting) with the ability to set team expectations for validating AI outputs for correctness, performance, and security Strong understanding of responsible AI use in engineering workflows, including data sensitivity considerations, secure handling of inputs/outputs, and adherence to resiliency and security expectations; experience coaching senior engineers/leads on compliant usage patterns and controls. Ability to convey design choices and results clearly and communicate effectively to stakeholders of various backgrounds Preferred qualifications, capabilities, and skills Experience with data, AWS and AIML engineering in commercial settings, preferably in financial sector Experience working on recommendation systems, LLM applications or other AI/ML systems Practical experience with Kubernetes, EKS, Docker, MLOps Prior exposure to LLMs, RAG, Knowledge Graph Technologies, OpenSearch and vector databases Prior experience collaborating with data scientists

We're looking for a hands-on AI engineer ready to take their career to new heights. Join the ranks of top talent at one of the world's most influential companies. As an Applied AI ML Lead - Vice President at JPMorgan Chase within the International Private Bank (IPB) Technology Artificial Intelligence and Machine Learning (AIML) Team, you provide deep engineering expertise and work across agile teams to enhance, build, and deliver trusted market leading AI products in a secure, stable, and scalable way. You will translate business problems into agentic AI and machine learning solutions, taking models from concept through to production grade services with measurable client and advisor impact. You will be responsible to the Head of AIML in IPB Tech for the end to end design, build, and production delivery of priority IPB AI/ML use cases, with particular focus on agentic AI applications, generative AI guardrails, and production ML supporting advisor and client journeys. Job responsibilities Owns end-to-end delivery of priority IPB AI/ML use cases, from problem framing and business case through to deployed, monitored production services with measurable advisor and client impact Leads the engineering build of agentic AI and LLM powered products serving IPB advisors and clients across the globe. Sets the engineering quality bar for the team's AI products through code reviews, technical design, and pairing with peers and junior engineers Establishes and operates Responsible AI controls in production (guardrails, evaluation frameworks, observability, and model risk controls) to firm wide standards Acts as a primary technical partner to IPB business stakeholders, surfacing new AI/ML opportunities and shaping them into funded workstreams Represents the AIML team in firm wide AI/ML governance and engineering forums; ensures cross-border, regulatory, and data privacy considerations are reflected in solution design Contributes to the team's GenAI education programme through training content, knowledge sharing sessions, and mentoring of junior engineers and interns Champions the firm's culture of diversity, Opportunity, inclusion, and respect Required qualifications, capabilities, and skills Formal training or certification in software engineering concepts and expert applied experience Advanced proficiency in Python and modern software engineering practices (testing, design patterns, code review, version control) Fluent with AI coding tools (e.g., Claude Code, GitHub Copilot) as a core part of day to day software development, with the judgement to know when to lean on them and when not to Hands on experience building, evaluating, and deploying machine learning models into production Practical experience with Large Language Models, including prompt engineering, RAG, fine tuning, agentic frameworks, skills. Demonstrated experience delivering system design, application development, testing, and operational stability for ML or data intensive systems Strong communication skills with confidence engaging senior business stakeholders and translating technical concepts for non technical audiences Experience applying new methods to determine solutions for complex technology problems across multiple technical disciplines MSc in Computer Science, Data Science, Engineering, or a related quantitative field Preferred qualifications, capabilities, and skills Postgraduate level qualification in data science, artificial intelligence, or machine learning Practical experience with CI/CD, containerization, and cloud native deployment patterns Experience within financial services technology, particularly wealth, private banking, or asset management Experience with Databricks, Kubernetes, or comparable ML / cloud platforms Experience designing or contributing to AI governance, model validation, or guardrail frameworks

Imagine what you could do here. At the company, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. The company is committed to delivering exceptional features and prioritizing user privacy. The Privacy Preserving Measurement & Machine Learning team works with teams across the company to develop state-of-the-art privacy-enhancing technologies for measurement and machine learning. We're looking for talented engineers to join us in this work. Description We are looking for an experienced on-device software engineer to join our team and help us improve privacy-preserving technologies to the company's products. Responsibilities Collaborate with cross-functional engineers to design and develop end-to-end measurement systems that meet the company's industry-leading privacy standards. Develop software that runs on billions of the company's devices, enabling training and evaluation of generative AI systems while preserving user privacy. Operate independently to solve complex problems at the intersection of privacy-preserving technology, applied cryptography, and machine learning. Employ strong technical background and experience in developing software on iOS or similar resource-constrained systems. Demonstrate strong interpersonal skills, including ability to influence and build consensus. Adapt to new problems and systems across a range of technologies. Preferred Qualifications Proven industry experience and a Bachelor's degree or equivalent in Computer Science or a related technical field. Passion for protecting customer privacy. Experience with privacy enhancing technologies such as differential privacy, multi-party computation, trusted execution environment, private federated learning, homomorphic encryption. Familiarity with or exposure to machine learning model post-training, evaluation, and inference. Minimum Qualifications Strong hands on experience in software development with proficiency in languages such as Python, Swift, and C++. Industry experience in iOS development or development on other embedded systems. Strong problem solving skills, creativity in finding effective solutions, and ability to collaborate with teams across the company. Track record of delivering large scale software systems from ideation and design through production deployment and operation.

Imagine what you could do here. At the company, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. the company is committed to delivering exceptional features and prioritizing user privacy. The Privacy Preserving Measurement & Machine Learning team works with teams across the company to develop state-of-the-art privacy-enhancing technologies for measurement and machine learning. We're looking for talented engineers to join us in this work. Description We are looking for an experienced on-device software engineer to join our team and help us improve privacy-preserving technologies to the company's products. Collaborate with cross-functional engineers to design and develop end-to-end measurement systems that meet the company's industry-leading privacy standards. Develop software that runs on billions of the company devices, that enable training and evaluation of generative AI systems while preserving user privacy. Operate independently to solve complex problems at the intersection of privacy-preserving technology, applied cryptography and machine learning. Successful candidates must possess a strong technical background and a keen interest or experience in developing software on iOS or similar resource constrained systems. Strong interpersonal skills and the ability to influence and build consensus are essential for success in this role. You will be working across a range of technologies, so adaptability to new problems and systems is a core skill. Preferred Qualifications Proven industry experience with a Bachelor's degree or equivalent experience in Computer Science or a related technical field. Passion for protecting customer privacy. Experience with privacy enchancing technologies such as differential privacy, multi-party computation, trusted execution environment, private federated learning, homomorphic encryption. Familiar with or exposure to machine learning model post-training, evaluating, and inference. Minimum Qualifications Strong hands-on experience in software development, with proficiency in one or more programming languages such as Python, Swift, C++. Industry experience of iOS development, or experience of development on other embedded systems. Strong problem-solving skills, creativity in finding effective solutions, and the ability to collaborate with teams across the company. A track record of delivering large-scale software systems from ideation and design through production deployment and operation.