Production Scheduler Enhancement Engineer Jobs

At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are energized by the opportunity to reinvent how they work. You don’t just use tools; you possess an innate curiosity, treating AI as a high-trust collaborator that is core to how you solve problems and accelerate your impact. We look for low-ego individuals who thrive in dynamic and fast-moving environments and move with an experimental mindset — who rapidly test emerging capabilities to discover simpler, more powerful ways to deliver results. At Snowflake, your role isn't just to execute a function, but to help redefine the future of how work gets done. Snowflake’s Release Engineering team builds and operates the systems that safely deliver infrastructure, platform, and product changes to production at global scale. We own the release platforms, rollout orchestration, and safety mechanisms that allow engineering teams across Snowflake to ship quickly while minimizing operational risk. Our mission is to make production deployments fast, safe, self-service, increasingly autonomous, and augmented by AI-driven intelligence and automation. This role sits at the intersection of developer productivity, distributed systems reliability, and large-scale multi-cloud infrastructure orchestration. At Snowflake, Release Engineering is a platform engineering function focused on building the systems, abstractions, and automation that make software delivery safe, scalable, and efficient across the company. In this role, you will Design and build continuous deployment and rollout infrastructure that safely ships changes across Snowflake’s large-scale, multi-cloud production environment. Build and evolve platform capabilities for progressive delivery, including staged rollouts, canarying, automated health checks, rollback controls, and guardrails that reduce blast radius during production change events. Improve engineering velocity by removi

About the role: We are seeking a Senior Backend Engineer with deep backend engineering expertise and proficiency in one or more major programming languages (e.g., Python, Java, Go, Rust, or Kotlin), along with a strong understanding of AI models and agents. As a core member of our AI Engineering team, you will collaborate with data scientists, ML engineers, and product managers to build scalable, production-ready infrastructure and APIs that power intelligent systems. What you'll be doing: As a Senior Backend Engineer in the AI Engineering team, you will: Build and maintain reliable, scalable backend services to support AI agent execution and orchestration. Develop AI agent systems for complex operational workflows using LangChain, LangGraph, LiteLLM, and Langfuse. Orchestrate a hybrid model stack that includes OpenAI and Google Gemini alongside self-hosted and fine-tuned LLMs like Gemma and Llama. Build and maintain integrations with clinical systems (FHIR, EMR). Drive observability and reliability using OpenTelemetry, Datadog, and Langfuse. Design APIs (GraphQL, REST), background workers, and event-driven systems that interface with AI inference engines and agent runtimes. Collaborate with Data Science, ML, and engineering teams to deploy AI features and improve the performance, scalability, and reliability of backend systems. Participate in code reviews, knowledge sharing, and mentoring to elevate the team’s technical capabilities. What we're looking for: 6+ years of backend engineering experience, with strong proficiency in more than one major programming language (such as Python, Java, Go, Rust, or Kotlin). Solid understanding of AI systems architecture and experience working in environments involving AI agents, LLMs, or inference pipelines. Proven experience in building and scaling backend APIs, microservices, and background jobs. Strong experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Redis), including schema des

FEQ327R502 The Manager, Specialist Solutions Architect will lead a team of Specialist Solution Architects and leaders in the Life Science vertical, who provide Specialist coverage for both our Solutions Architect (SA) teams and Delivery Solutions Architect (DSA) team. Your experience when partnering with the pre-sales technical team and leaders will help drive technical wins and accelerate Databricks DBU consumption. You will be responsible for guiding and empowering your team to communicate complex, outcome-based results that drive consumption and help our customers achieve their desired outcomes. The impact you will have: Hiring and building the Specialist Solutions Architect team, scaling the designated field engineering segment organization without sacrificing quality Build a collaborative culture within a hyper-growth team to embody and ensure Databricks' company values Drive Databricks product adoption and accelerate use cases to production within the Life Sciences vertical. Collaborate closely with cross-functional teams, including Sales, Marketing, Support, Product Development, Operations, and other FE teams, to strategize and align efforts towards achieving HLS vertical's incremental consumption target and commit target. What we look for: 2+ years leadership experience building and guiding teams Demonstrated expertise in designing and implementing complex, large-scale solutions within the healthcare and life science industries, with a solid understanding of the specific challenges and data requirements in the HLS vertical. Strong knowledge of HLS-specific regulations, such as HIPAA, GDPR, and industry standards like HL7, FHIR, and DICOM. Familiarity with life science-related use cases and topics, including genomics, bioinformatics, clinical trials, drug discovery, real-world evidence, and precision medicine. In-depth understanding of healthcare-related use cases and topics, such as electronic health records (EHR), telemedicine, medical ima

Our vision is to transform how the world uses information to enrich life for all . Micron Technology is a world leader in innovating memory and storage solutions that accelerate the transformation of information into intelligence, inspiring the world to learn, communicate and advance faster than ever. Responsibilities and Tasks: • Establish and improve process condition and technology. • Upgrade process capability and reduce production cost. • Establish and modify process management projects. • Set up process parameters for a variety of semiconductor equipment. • Evaluation, promotion and planning of new equipment / materials. • Abnormal analysis and improvement. AI Relevant Job Responsibilities: - Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements. - Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work. - Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business About Micron Technology, Inc. We are an industry leader in innovative memory and storage solutions transforming how the world uses information to enrich life for all . With a relentless focus on our customers, technology leadership, and manufacturing and op

What you’ll do Partner with medical image reconstruction scientists / engineers to build ML components that improve reconstruction quality, speed, robustness, or quantitative accuracy. Define training/evaluation pipelines, datasets, and metrics that map to user needs and design requirements. Productionize models: inference performance, reproducibility, monitoring for drift/regressions, and safe fallbacks. Collaborate on hybrid algorithms, incorporating physics and learned priors, denoisers, learned regularizers, and quality estimation. Help build tooling for rapid experimentation as well as rigorous verification of algorithm changes. What we’re looking for Strong applied ML experience plus comfort with signal processing / imaging or adjacent domains. Ability to move fluidly between research prototypes and production-quality systems. Strong evaluation discipline: metrics, ablations, data leakage avoidance, and reproducibility. A demonstrated track record of applying ML to physics-based or inverse problems (i.e., shipped projects, a portfolio, or publications.) Useful experience ML for imaging/inverse problems (or adjacent) with strong evaluation discipline and comfort with GPU performance constraints. Pragmatic production mindset: reproducible training/inference, regression testing, and safe deployment in high-stakes contexts. A background in computational physics or scientific computing. Leverage ML-based methods such as PiNNs and Neural Operators to solve partial differential equations arising in ultrasound simulation and imaging. Experience in Agentic-SciML is a plus. Hands-on experience with data curation for ML: building datasets from messy, real-world sources, defining ground truth, and managing labeling or simulation pipelines. Background in data assimilation: combining observations with physics-based models (Kalman filtering, variational methods, ensemble approaches, or learned variants).

The Perception team is pioneering the development of a multi-modality foundation model to drive the next generation of autonomous system intelligence. As a Machine Learning and System Optimization Engineer, you will orchestrate and allocate overall system capacity to various core perception models running on-bot, as well as drive large initiatives that allow for more efficient inference by sharing various parts of the perception stack with one another. You will focus on bringing highly efficient, production-ready large-scale models to our on-vehicle stack. We are looking for experts with hands-on experience compressing, accelerating, and deploying complex models, including LLMs, VLMs, or foundation models, for power- and thermal-constrained vehicle SoCs. In addition, you will optimize ML models, write custom CUDA kernels, and build highly concurrent inference code to ensure real-time, deterministic execution on edge devices. In this role, you will: Allocate and distribute system resources (CPU/GPU/interconnect) to various models and inference engines running on the robot. Spearhead cross-cutting initiatives that allow for better compute utilization through sharing/fusing models and better scheduling strategies. Optimize large-scale models (Multi-Modal Sensor Fusion models, LLMs, VLMs) using advanced quantization (PTQ, QAT), pruning, mixed-precision inference frameworks, and parameter-efficient fine-tuning (LoRA, QLoRA). Architect and implement model conversion and compilation pipelines using TensorRT for edge deployment. Write production-level, low-latency, and memory-safe C++ and CUDA code for real-time inference on vehicle systems. Qualifications: Deep experience in system and performance optimization in CPU/GPU systems designed for low latency or high throughput. Deep expertise in working with real-time systems & required

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

Software is eating the world, but AI is eating software. We live in unprecedented times – AI has the potential to exponentially augment human intelligence. Every person will have a personal tutor, coach, assistant, personal shopper, travel guide, and therapist throughout life. As the world adjusts to this new reality, leading platform companies are scrambling to build LLMs at billion scale, while large enterprises figure out how to add it to their products. To make them safe, aligned and actually useful, these models need human eval and reinforcement learning through human feedback (RLHF) during pre-training, fine-tuning, and production evaluations. This is the main innovation that’s enabled ChatGPT to get such a large headstart among competition. At Scale, our products include the Generative AI Data Engine, SGP, Donovan, and others that power the most advanced LLMs and generative models in the world through world-class RLHF, human data generation, model evaluation, safety, and alignment. The data we are producing is some of the most important work for how humanity will interact with AI. At the foundation of these products is the Identity Engineering team. In this role, you will help support the design and development of core software systems specifically focused on identity, access management, authorization, and authentication. You’ll also get widespread exposure to the forefront of the AI race as Scale sees it in enterprises, startups, governments, and large tech companies. You will: Drive the design, and implementation of our identity infrastructure to ensure secure authentication and authorization across enterprise systems. Build software for authentication mechanisms such as Single Sign-On (SSO), Multi-Factor Authentication (MFA), and federated identity solutions (SAML, OAuth, OpenID Connect). Build software for authorization mechanisms such as Relation-based access control (ReBAC), Attribute-based access control (ABAC), Role-based access cont

Opportunity ThermalWorks LLC is seeking an experienced Quality Assurance Manager to serve as the technical quality authority and liaison across our customer field sites, European contract manufacturer sites and internal quality control function. This is a cross-functional, high-visibility role that sits at the intersection of manufacturing, field service, and quality leadership. The ideal candidate brings deep hands-on experience with mission-critical mechanical systems — particularly hydronic cooling, chiller platforms, and data center infrastructure — combined with the discipline and communication skills to document findings clearly and present them to leadership. This role is hands-on and will require mechanical knowledge of HVAC systems as well as quality related processes such as 8D problem solving and Six Sigma methodologies. This position is preferably based in Barcelona, but can also be based in Madrid or Bilbao. This role has a travel requirement of 20-40% depending on where based. Key Responsibilities Include but are not limited to: Factory Quality Support new and existing production at ThermalWorks manufacturing operations in Europe to identify quality concerns for first article inspections or before production units ship Review assembly, wiring, piping, and commissioning documentation against engineering specifications and approved submittals Coordinate findings with factory leadership and flag hold conditions requiring resolution prior to release Document inspection outcomes and provide written reports to the Director of Quality Customer Site Quality Perform on-site QA/QC inspections at customer data center locations to verify ThermalWorks equipment installation, commissioning, and service work meets required standards Work with EU Director of Operations when customer issues arise Drive 8D problem solving for technical customer issues and coordinate investigation and corrective actions with TW Engineering and Operations personnel Create cus

The eBPF APM team is building a zero-instrumentation observability solution that automatically discovers services on every host, supports both plaintext and TLS-encrypted traffic, classifies Layer 7 protocols, decodes service-level traffic, and reports RED (requests, errors, duration) metrics. Leveraging deep expertise in eBPF, the team operates across a wide range of Linux kernel versions, distributions, and complex customer environments. In addition to low-level networking, the team solves challenges related to protocol versioning, TLS detection across diverse languages and runtimes, and resilient performance in production systems We’re looking for a senior engineer with strong systems-level thinking and a good understanding of Linux. You should be comfortable working close to the kernel, ideally with experience in eBPF, or with a strong desire to dive into it. Proficiency in C/C++/ Go is essential, and familiarity with networking protocols, TLS internals, or distributed tracing is a strong advantage. You’ll join a high-impact team tackling ambitious technical challenges—like decoding traffic across multiple protocols, and ensuring high-fidelity metrics in complex, real-world environments. You’ll be expected to lead design and implementation efforts, contribute to roadmap planning, and collaborate across teams to ensure our solution remains robust, scalable, and frictionless for our users. This role is a great fit for engineers who thrive on low-level, performance-sensitive problems, and want to shape the future of observability through cutting-edge kernel technology. At Datadog, we place value in our office culture - the relationships that it builds, the creativity it brings to the table, and the collaboration of being together. We operate as a hybrid workplace to ensure our employees can create a work-life harmony that best fits them. What You’ll Do: Design and build core components of our zero-instrumentation APM product using eBPF and Go Develop systems to aut

Everpure (NYSE: P) has evolved from storage pioneer to data platform, closing fiscal 2026 with $3.7 billion in revenue, its first billion-dollar quarter, and accelerating growth into FY27. Our strategic agenda spans the companies defining the next era of technology - hyperscalers, AI labs, the AI hardware supply chain, data platform providers, and the broader AI ecosystem. This type of work—work that changes the world—is what the tech industry was founded on. So, if you're ready to seize the endless opportunities and leave your mark, come join us. THE ROLE Join the Portworx team and play a pivotal role in delivering our highest-quality suite of products. In this role, you will contribute to building clean, robust code with a relentless focus on quality and customer success. You will be instrumental in developing a new SaaS platform designed to provide a secure, consistent, and best-in-class experience for customers purchasing and utilizing various Portworx offerings. As a core developer, you will take ownership of designing and implementing innovative features and products across the Portworx portfolio. WHAT YOU’LL DO Design & Develop SaaS Microservices: Build, scale, and integrate new features into Portworx products, ensuring seamless alignment with our distributed system architecture. Own the Lifecycle: Lead end-to-end engineering efforts, including design reviews, code reviews, unit/functional testing, documentation, and managing CI/CD deployment pipelines. Collaborate Globally: Partner closely with cross-functional peers and stakeholders (from Product Management to early-adopter customers) to take solutions from initial concept to production. Drive Iterative Quality: Take full ownership of feature development by proactively adapting to customer feedback and resolving issues identified during testing and deployment. Innovate & Experiment: Research and experiment with emerging technologies to push boundaries, optimize cloud infrastructure, and pione

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. About the Role We are seeking a technical, strategic and creative Partnerships Product Marketing Manager to drive the success of our ecosystem partners. In this role, you will work closely with our partnerships, product and engineering teams and with emerging technology companies to bring differentiated joint solutions to market. You will be responsible for shaping partner narratives, creating impactful content, and enabling joint go-to-market programs that amplify our reach. The ideal candidate combines storytelling skills, technical acumen, and the ability to collaborate across partner and internal teams. Key Responsibilities Partner Storytelling & Content Develop compelling technical blog posts, white papers, solution briefs, and customer success stories highlighting the value of joint solutions. Translate technical integrations into clear, differentiated messaging for both technical and business audiences. Enablement & Training Build and deliver enablement programs to arm partner sales teams with the tools, messaging, and collateral they need to position and sell our solutions. Create sales playbooks and battlecards tailored to each partner’s ecosystem. Joint Go-to-Market Campaigns Plan and execute co-marketing campaigns with partners, including webinars, events, solution launches, and demand-generation activities. Manage partner marketing calendars and ensure alignment with key product milestones. Cross-Fu

Generative AI Architect Location: Charlotte, NC | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to containerized and distrib

Generative AI Architect Location: New York, NY & Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to c

Generative AI Architect Location: New York, NY & Orlando, FL | Practice Area: Technology & Engineering | Type: Permanent Shape the architecture of enterprise-scale generative AI solutions at the forefront of innovation The Role As part of Capco’s Technology Delivery Team, you will apply deep expertise in architecture, AI, and modern engineering practices to design and deliver next-generation solutions. As a Generative AI Architect, you will lead the definition and implementation of scalable, secure, and enterprise-grade AI systems, guiding projects from concept through to production while aligning technology with strategic business goals. What You’ll Do Define and deliver enterprise-wide architecture for generative AI and agentic systems aligned to business objectives Design scalable, modular solution patterns and integrate foundation models into enterprise environments Architect and implement agentic AI systems, including workflows, orchestration, and system integrations Establish robust cloud-native infrastructure and MLOps pipelines for deployment, monitoring, and lifecycle management Collaborate across teams, mentor colleagues, and contribute to innovation and thought leadership in AI What We’re Looking For Bachelor’s or Master’s degree in Computer Science, AI/ML, or a related field 10+ years of experience in software architecture, including hands-on work with AI/ML systems Strong expertise in generative AI, foundation models, and agentic AI frameworks Proficiency in Python and experience with leading AI/ML frameworks and cloud platforms (AWS, Azure, or GCP) Proven ability to communicate complex technical concepts and influence technical decision-making WIllingness to work in our office 3 days/week Bonus Points For Experience with prompt engineering and advanced RAG-based architectures Familiarity with vector databases and unstructured data processing techniques Experience implementing MLOps frameworks and production-grade AI systems Exposure to c