Opportunity: Get Well is seeking a highly skilled and proficient Staff AI Engineer to drive the development and implementation of advanced AI solutions. This role focuses on the technical execution of AI projects, leveraging expertise in Large Language Models (LLMs), multimodal AI systems, and agentic systems to create innovative healthcare solutions. You will work closely with AI engineering teams, product teams, and cross-functional stakeholders to translate technological capabilities into impactful healthcare solutions, serving as a key technical liaison. Responsibilities: AI Solution Development Design, develop, and implement AI solutions leveraging unimodal and multimodal Large Language Models (LLMs) and agentic systems. Develop and integrate agentic systems using frameworks like CrewAI, LangChain, and LangGraph to enable autonomous decision-making and workflow automation. Enhance product ecosystems by incorporating emerging AI technologies to improve functionality and user experience. Execute model training, fine-tuning, and optimization of inference engines for high-performance AI systems. Ensure technical excellence in AI solution design and implementation. Evaluate and integrate emerging AI technologies into existing systems. Cross-Functional Collaboration Serve as primary technical liaison between AI engineering teams and product teams Translate technical capabilities into product requirements and user-centric solutions Help facilitate communication and alignment across engineering, product, and clinical teams Drive collaborative innovation and knowledge sharing Infrastructure and Optimization Optimize cloud-based AI infrastructure for scalability, performance, and reliability. Implement best practices for efficient AI system deployment and maintenance, including agentic workflows. Performance and Quality Assurance Establish and maintain rigorous testing and validation protocols for AI models Drive continuous improvement in AI model accuracy, efficie
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To lead and manage the maintenance, reliability, and performance optimization of Steam Turbine Generators and associated auxiliaries within a large thermal power plant. The role is responsible for ensuring maximum equipment availability, minimizing forced outages, executing preventive and predictive maintenance strategies, improving operational efficiency, and ensuring adherence to safety, reliability, and statutory compliance standards. Source: Adani Group | Job ID: 58649
About the Team DoorDash is building the world’s most reliable on-demand logistics platform. As we continue to expand our Engineering organization globally, we’re looking for Staff Backend Engineers to build and evolve the large-scale, highly available systems that power DoorDash’s three-sided marketplace of consumers, merchants, and Dashers. Our engineers solve complex technical and business problems across a global platform that operates 24/7 and supports millions of users. About the Role We’re looking for Staff Backend Engineers to join Product and Product Platform teams across DoorDash. Engineers on Product teams work at the intersection of product and infrastructure, translating complex business problems into scalable technical solutions. Engineers on Product Platform teams build the foundational systems, services, and capabilities that enable product teams to move quickly and reliably. As a Staff Engineer, you will set technical direction, lead complex initiatives across teams, and shape the architecture and long-term roadmap of critical systems. You’ll partner closely with Engineering, Product, Design, and other cross-functional stakeholders to evaluate trade-offs and deliver solutions that maximize customer and business impact. You will also raise the technical bar across the organization by mentoring engineers, improving engineering practices, and helping teams navigate ambiguous, high-impact technical challenges. This is a hybrid role with some in-office time expected. You will report to an Engineering Manager. You're excited about this opportunity because you will… Develop, release and run large-scale web applications Develop and define the backend architecture and tech stack for a product area Improve performance, reliability, scalability and security for our backend systems Be involved in transitioning our monolithic codebase to a microservice-based architecture Completely disrupt logistics by tackling bleeding-edge, technical problems We're excited abou
We’re building a world of health around every individual — shaping a more connected, convenient and compassionate health experience. At CVS Health®, you’ll be surrounded by passionate colleagues who care deeply, innovate with purpose, hold ourselves accountable and prioritize safety and quality in everything we do. Join us and be part of something bigger – helping to simplify health care one person, one family and one community at a time. Position Summary The Lead Director, Agile Practice Management leads end-to-end delivery of a portfolio of strategic and regulatory technology initiatives within Aetna Commercial and Distinct Client Segments (DCS) Delivery. This role is focused on delivery execution, driving outcomes, financial discipline, and team-of-teams performance. The Lead Director balances strategic portfolio oversight with hands-on program leadership. They partner with Engineering, Product, Architecture, Finance, and business leaders to set priorities, manage investments, and turn strategy into predictable, measurable results. This leader develops Program Managers, Project Managers, and Scrum Masters and serves as the central connector between technology leaders and business stakeholders. They stand up and mature programs, set consistent governance and reporting standards, and manage portfolio financials across capital and operating expense, including forecasting, variance management, capacity planning, and investment trade-offs. Success is measured by delivery predictability, financial transparency, portfolio health, and a culture of accountability and continuous improvement. Location: Hybrid in Hartford, CT office preferred. Will consider remote. Required Qualifications 10+ years of experience in program and portfolio management, including managing large-scale, complex te
NVIDIA is seeking outstanding Research Interns to join the Data-Driven AI for Robotics (DAIR) group. The focus is on learning embodied skills from large-scale human data. Our objective is to develop AI systems that capture, understand, and reproduce complex human motion and interaction skills across physical and digital embodiments, including humanoid robots and animated characters. Our research spans the full stack: reconstructing human motion and human-object interactions from video; generating diverse, controllable character behaviors; transferring motion across embodiments; and training physically grounded controllers for humanoid robots and interactive virtual characters. You will collaborate with a passionate and supportive research team that consistently produces influential work published at leading computer vision, machine learning, graphics, and robotics conferences. You will also have the opportunity to collaborate with world-class research and product teams across NVIDIA, following our strong “one-team” culture. What you'll be doing: Innovate and implement novel AI algorithms that transform large-scale human data into controllable motion and interaction skills across physical and digital embodiments. Develop robust, scalable training and inference pipelines for motion reconstruction, generation, retargeting, and character and robot control. Build methods that transfer human skills to humanoid robots, including whole-body loco-manipulation and dexterous manipulation. Maintain a close, collaborative relationship with your mentor(s). Publish your research findings at leading computer vision, machine learning, graphics, and robotics conferences. Partner with product teams to enable effective technology transfer of your work. Research Topics Include: Human motion and human-object interaction reconstruction, synthesis, and generatio
Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Senior or Lead Bioinformatics Scientist to join the team building the technology at the heart of that effort. You will work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. You will help advance the state-of-the-art and drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Develop and validate new algorithms to analyze large multimodal epigenomic datasets Drive research analyses through implementation, testing and performance evaluation, including developing new features within existing pipelines Work with sequencing and clinical data from large cohorts, ensuring data integrity and quality control Partner with molecular biologists and clinical scientists to solve challenging, open-ended problems Visualize results and present complex findings to both technical and non-technical audiences Contribute to the team’s standards for code quality and reproducibility QUALIFICATIONS: Ph.D. in Bioinformatics, Computer Science, Biology, or a related field; alternatively a Bachelor’s or Master’s degree with at least 4 years of professional experience Track record developing and validating analysis workflows for high-throughput sequencing data Experience applying and evaluating statistical and ML methods to large datasets Strong quantitative reasoning and data analysis skills, applied effectively to real scientific problems. Software development experience, including proficiency in Python and its scientific computing ecosystem Fluent using Linux command-line tools and cloud computing environments Strong verbal and written communication skills Preferred Experience Working knowledge of DNA methylation and other epigenomic data Experience with cell-free DNA and liquid biopsy samples Ba
Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group Prototype, test and productionize ML models using scalable infrastructure Own key technical deliverables within larger projects and help shape the team’s research roadmap Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies Keep raising the bar through code and design reviews across projects Translate complex results into clear stories for technical and non-technical audiences Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence QUALIFICATIONS: PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data Proven track record of innovation and technical leadership in complex method development projects Expertise in deep learning and multimodal foundation models Proficient in Python and its scientific computing ecosystem Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology Excellent co
Natera’s Research team is building tests that can detect many cancers from a single blood draw. We are looking for a Staff Machine Learning and Bioinformatics Scientist to help design the models at the heart of that effort. You’ll work with large-scale, multi-modal genomic datasets from clinical cohorts and partner closely with molecular biologists and clinical scientists. Your research will advance the state-of-the-art and you will drive new methods from prototype, through scalable implementation, toward clinical validation and, ultimately, to patients. PRIMARY RESPONSIBILITIES: Lead the development of novel statistical and machine learning methods for cancer signal detection on multi-modal genomic data Build interpretable, well-calibrated models, setting the standard for uncertainty estimation and reproducibility across the group Prototype, test and productionize ML models using scalable infrastructure Own key technical deliverables within larger projects and help shape the team’s research roadmap Collaborate closely with molecular biologists and clinical experts on design and analysis of experiments and validation studies Keep raising the bar through code and design reviews across projects Translate complex results into clear stories for technical and non-technical audiences Mentor junior scientists and champion a culture of curiosity, collaboration, and scientific excellence QUALIFICATIONS: PhD in Computer Science, Mathematics, Bioinformatics, or a related quantitative field with 6-12 years of experience post-PhD Hands-on experience developing novel statistical / ML analysis methods applied to complex biological data Proven track record of innovation and technical leadership in complex method development projects Expertise in deep learning and multimodal foundation models Proficient in Python and its scientific computing ecosystem Scientific rigor throughout the R&D process, with eagerness to teach and learn new computational methods and biology Excellent co
About the Job Turn complex AI workload signals into faster, more efficient systems at data center scale. As a Senior AI Performance Engineer, you will analyze and optimize AI training and inference workloads across large-scale distributed systems. Your work will connect compute, memory, communication and software behavior. You will own complex performance investigations from problem definition through validation. You will turn profiling, benchmarking and modeling results into improvements engineers can build from. You will design benchmarks, investigate system bottlenecks and optimize distributed communication software across technologies such as MPI, NCCL, UCX and RDMA. Your work will help Graphcore deliver efficient, reliable AI systems for large-scale deployment. This role gives you rare scope across hardware, software, networking and system architecture. It is based in Austin, Texas. The team and culture The System Engineering Performance team architects, evaluates and optimizes high-performance infrastructure for large-scale data center deployments. The team works across the computing stack to understand real system behavior. Work moves through evidence, ownership and clear technical judgment. You will define investigations, coordinate across teams and validate impact with reliable performance data. Decisions are shaped through benchmarks, models, simulations and practical engineering tradeoffs. The team values engineers who think big, act fast, take responsibility, speak up and lead beyond their own area. What we’re looking for · Strong experience profiling and optimizing AI, machine learning or high-performance computing workloads. · Experience with distributed systems and communication libraries such as MPI, NCCL, UCX or libfabric. · Strong C++ and Python skills, including reliable tools or performance-sensitive software. · Deep understanding of compute, memory and communication behavior in large-scale systems. · Ability to own complex technical work and coo
Become a part of our caring community Most AI engineering jobs are a thin wrapper around a model API. This role is different. We build the platform that transforms millions of clinical documents into trusted, actionable data. Our systems use large language models (LLMs) to read medical records, extract structured facts, answer complex questions with citations back to the source document, and route ambiguous cases to human experts for review. Our users make decisions that impact real healthcare outcomes, so “good enough” is not good enough. Building AI systems that are accurate, reliable, auditable, and scalable is at the core of this role. As a Senior AI Applied Engineer, you will design, build, deploy, and operate production AI systems used at scale within one of the largest health insurers in the United States. You will own solutions end-to-end, from user experience and APIs to model orchestration, evaluation frameworks, infrastructure, and production operations. Why Join Us Build production AI systems where LLMs are in the critical path, not just demos or proofs of concept. Work on extraction, retrieval, agentic workflows, and human-review systems that process real healthcare data at scale. Own projects end-to-end across frontend, backend, AI orchestration, infrastructure, deployment, and operations. Solve challenging problems around accuracy, explainability, traceability, and reliability in regulated environments. Ship quickly in a small, high-impact team that embraces AI-assisted development and rigorous quality standards. Build systems that continuously improve through expert feedback, evaluations, and human-in-the-loop workflows. Key Responsibilities Design, develop, and deploy full-stack AI-powered application
At Rockstar Games, we create world-class entertainment experiences. Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. Rockstar New England is on the lookout for a passionate Workplace Coordinator. As part of the Workplace Services team, you will provide key coordination of the day-to-day operation of the site and its facilities services. This is a six (6) month contract position, in-office based out of Rockstar’s development studio in Andover, MA. WHAT WE DO The Rockstar Workplace Services team (WPS) is responsible for ensuring the office, building, programs, and services work harmoniously together to support the core business. We create a creative, supportive, and safe working environment for the staff at Rockstar. We manage and develop a variety of services and programs, including food & beverage, physical security, building maintenance, furniture, security, cleaning, space utilization and operational support. We ensure the site complies with all relevant statutory guidance and legislation. We partner with senior leadership to drive proactive real estate growth strategies, leasehold improvement, and capital expenditure projects. RESPONSIBILITIES Review and monitor internal ticketing system, provide timely updates, record actionable steps and ensure the needs have been met for the end users. Proactively identify issues through walkthroughs; prioritize and address them through self-performance or outsourced vendors. Coordinate, plan, and execute assigned projects ensuring all work is done to a high standard, and progress updates are regularly provided. Perform quality control on assigned services. Coordinate vendor work schedules as required, and conduct follow up tasks for project completion. Conduct checks and audits of the site f
itD is seeking an Engineering Program Manager, Data & Analytics to lead strategy and execution for large-scale analytics and data engineering initiatives supporting data-informed decision-making. The ideal candidate will bring deep experience in technical program management, data engineering and analytics lifecycles, and cross-functional delivery, with a track record of driving complex programs from strategy through execution. Location: Onsite — Bay Area, CA preferred. Pay rate: $36.36/hr We provide comprehensive medical benefits, a 401k plan, paid holidays, and more. Please note that we are only considering direct W2 candidates at this time, as we are unable to offer sponsorship. Responsibilities: Lead cross-functional technical programs spanning data engineering, data science, analytics, and customer-facing systems. Drive strategy, roadmap development, execution, and delivery for complex, large-scale data and analytics initiatives. Coordinate engineering, data science, product, and business stakeholders to establish priorities, dependencies, milestones, and deliverables. Analyze data definitions, transformations, modeling, and downstream analytics impacts to ensure data remains accurate, meaningful, and fit for purpose. Manage program status reporting, roadmap reviews, engineering reviews, and stakeholder communications. Navigate fast-paced and ambiguously defined initiatives involving multiple customers, partners, and technical teams. Identify program risks, dependencies, and execution challenges while driving timely resolution and alignment. Internal Responsibilities: Attend regular internal practice community meetings. Collaborate with your itD practice team on industry thought leadership. Complete client case studies and learning material (blogs, media material). Build out material to contribute to the Digital Transformation practice. Attend internal itD networking events (in person and virtual). Work with leadership on career fast-track opportuniti
As a Staff Research Scientist within Datadog AI Research (DAIR), you will drive research in foundation models and world models as a hands-on individual contributor. You will advance large-scale pre-training and multimodal learning across the diverse signals generated by distributed systems, including metrics, traces, logs, topology, and events. You will set the technical direction for ambitious research programs, raise the technical bar for the researchers and research engineers around you, and collaborate with Datadog's product and engineering teams to translate research advances into products. What You'll Do: Drive research in foundation models, world models, and multimodal learning, shaping the technical direction of ambitious research programs grounded in observability Own research problems end to end, from framing the question through experimentation, model development, and evaluation Train large-scale multimodal models on diverse telemetry data, including metrics, logs, traces, topology, events, and other non-text modalities Advance approaches to pre-training, representation learning, world modeling, scaling, and evaluation for models that learn the dynamics of complex distributed systems Raise the technical bar across the team by reviewing research directions, mentoring researchers and research engineers, and setting standards for experimental rigor Collaborate with cross-functional teams across Research, Product, and Engineering to translate research advances into scalable Datadog capabilities Contribute to research publications, present at top-tier conferences such as NeurIPS, ICLR, and ICML, and help open-source key model artifacts and benchmarks Who You Are: You hold a PhD in Computer Science, Machine Learning, or a related field, or have equivalent experience, with deep expertise in areas such as foundation models, world models, multimodal learning, or generative modeling You have driven technically ambitious research at meanin
At Rockstar Games, we create world-class entertainment experiences. Become part of a team working on some of the most rewarding, large-scale creative projects to be found in any entertainment medium - all within an inclusive, highly-motivated environment where you can learn and collaborate with some of the most talented people in the industry. Rockstar New England is on the lookout for detail-oriented Admin Coordinator with a passion for operational excellence who thrives in a dynamic environment. This role will see you working to oversee administrative activities, streamline office procedures, manage inventory and coordinate periodic company outings. This is a full-time, in-office position based out of Rockstar’s development studio in Andover, MA. WHAT WE DO The Admin Team ensures the smooth running of the day-to-day studio operations by working closely with stakeholders to proactively understand their needs. We act as the primary point of contact for internal staff, vendors, and clients; we anticipate the needs of the studio, providing solution-oriented support to the Studio and our visitors in an efficient manner. We support Rockstar’s goals and values, demonstrating them in all work activities and interactions on behalf of the company. RESPONSIBILITIES Act as the primary Admin Team member for the studio, supporting local operations while collaborating closely with the wider regional team to ensure consistent service delivery. Deliver front of house and guest services, coordinating visitor management, access coordination and guest arrivals ensuring a welcoming studio experience. Coordinate business travel, accommodation, transport and hospitality arrangements while maintaining travel boards and trackers, to ensure effective planning and visibility. Maintain relationships with travel and accommodation vendors to support effective delivery of travel services. Maintain accurate files, records and documentation in line with established p
Overview: Guidepoint is investing in applied AI across its research platform. We're building conversational AI systems that interact with our global expert network at scale — combining real-time voice, LLM-driven orchestration, and retrieval over large proprietary datasets. You'll be an early engineer on a new initiative: taking working prototypes to production and shaping the architecture as the product scope grows. This is a hands-on role with broad ownership, close to product and leadership. This role is hybrid in our Toronto Office What You'll Do: Real-time conversational AI: voice- and chat-based agents with low-latency requirements, built on modern telephony and real-time media infrastructure. LLM orchestration: agentic systems that pursue goals over multi-turn conversations, with hard behavioral guarantees enforced in code — not just prompts. Multi-channel session management: stateful user interactions that move seamlessly across channels. Retrieval and grounding: connecting LLM systems to large internal knowledge assets, with structured data flowing back. Evaluation infrastructure: measuring conversational quality against human baselines and gating rollouts on metrics, not vibes. Own services end-to-end: design, implementation, deployment (Kubernetes/Azure), and operations, including latency-sensitive real-time workloads. Design and tune LLM pipelines: context engineering, structured outputs, model selection, cost/latency tradeoffs across vendors. Build the eval loop and treat quality as a number: define metrics, run experiments, gate releases on them. Integrate third-party AI and voice vendors behind clean abstractions so providers stay swappable. Partner with product and compliance stakeholders to encode domain rules into the system. Set engineering patterns for a growing team: code review, observability, incident habits. What You Have: 6+ years of software engineering, with 2+ years building LLM-powered products in production (not notebooks): orchestratio
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