Software Engineer Ml Infrastructure Jobs

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We are looking for a Field Application Engineer to serve as the technical bridge between Tenstorrent and customers across Southeast Asia. Based in Singapore, you will work closely with customers, partners, sales, and global engineering teams to understand AI and machine learning workloads, guide technical evaluations and deployments, troubleshoot issues across hardware and software, and help customers realize the performance of Tenstorrent’s AI platforms. This is a highly visible, customer-facing role that combines hands-on technical problem solving, solution development, and regional relationship building, with regular travel throughout Southeast Asia. This role is remote, based out of Singapore. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A customer-focused technical professional who can build trust with application developers, engineering teams, and business stakeholders. Comfortable translating complex AI/ML hardware and software concepts into clear recommendations for both technical and non-technical audiences. A proactive and self-directed problem solver who can coordinate internal teams, external service providers, and customer sta

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language

AI Engineer Role Overview: As an AI Engineer at Particle41 you will design, develop and deploy machine-learning and deep-learning models/solutions (including generative-AI) that address complex business problems. You will collaborate with data scientists, data engineers, software engineers and client stakeholders. You will also build scalable pipelines, ensure production readiness, monitor performance and iterate proactively. In This Role, You Will: Lead end-to-end development of AI/ML models: from data ingestion & preprocessing to model training, evaluation, deployment and monitoring. Build generative-AI solutions (RAG, Agentic Workflows, MCP Servers, Conversation AI Agents) aligned with business goals. Work closely with data engineering teams to build/maintain data pipelines, feature stores and orchestration frameworks. Develop and integrate AI models into production systems (APIs, microservices, cloud deployments). Optimize models/solutions for performance, scalability, robustness and cost-efficiency. Monitor models/ solutions’ performance in production (drift, bias, fairness, reliability) and implement remediation. Document model design, experiments, data provenance and solution rationale. Stay abreast of latest AI/ML research, frameworks, tools (e.g. LangChain, LangGraph, MCP Clients/Servers, Agents SDKs, LiveKit etc.) and propose innovative ideas. Work directly with clients to understand problem statements, translate business requirements into AI solutions, and clearly communicate results. Skills and Experience We Value: Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science, or related field. 3+ years of hands-on experience in AI/ML model development and deployment. Strong programming skills in Python and experience with major ML/AI frameworks (TensorFlow, PyTorch, scikit-learn, LangChain, LangGraph). Experience with vector databases (e.g., Pinecone, FAISS), RAG and Agentic workflows. Experience building or fine-tuning Large Language

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is seeking talented Physical Design Engineers to implement high-performance blocks for our industry-leading CPU and AI/ML architectures. You'll own the complete implementation flow from synthesis to tapeout, working alongside world-class engineers to push the boundaries of performance, power, and area. If you're passionate about crafting silicon that powers the future of AI computing and thrive on solving complex design challenges, we want you on our team. This role is hybrid , based out of Austin, TX, Santa Clara, CA or Fort Collins, CO. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are A hands-on engineer with deep expertise in SOC/ASIC physical design and a track record of successful tapeouts. Passionate about optimizing PPA through innovative implementation techniques and close RTL collaboration. Strong problem solver who excels at debugging complex issues across design hierarchies. Collaborative team player who thrives in fast-paced, technically challenging environments. What We Need BS/MS/PhD in EE/ECE/CE/CS with proven experience in synthesis, PnR, and timing closure on taped-out designs. Expertise with industry-

About Anthropic Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. About the role: Running machine learning (ML) algorithms at our scale often requires solving novel systems problems. As a Performance Engineer, you'll be responsible for identifying these problems, and then developing systems that optimize the throughput and robustness of our largest distributed systems. Strong candidates here will have a track record of solving large-scale systems problems and will be excited to grow to become an expert in ML also. You may be a good fit if you: Have significant software engineering or machine learning experience, particularly at supercomputing scale Are results-oriented, with a bias towards flexibility and impact Pick up slack, even if it goes outside your job description Enjoy pair programming (we love to pair!) Want to learn more about machine learning research Care about the societal impacts of your work Strong candidates may also have experience with: High performance, large-scale ML systems GPU/Accelerator programming ML framework internals OS internals Language modeling with transformers Representative projects: Implement low-latency high-throughput sampling for large language models Implement GPU kernels to adapt our models to low-precision inference Write a custom load-balancing algorithm to optimize serving efficiency Build quantitative models of system performance Design and implement a fault-tolerant distributed system running with a complex network topology Debug kernel-level network latency spikes in a containerized environment Deadline to apply: None. Applications will be reviewed on a rolling basis. The annual compensation range for this role is listed below. Fo

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Field Application Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is hybrid, based out of Tokyo, Japan. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. This role is hybrid, based out of Tokyo, Japan. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how t

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. About the Role We are looking for experienced EDA/CAD engineer with hands-on AI, ML, or LLM experience who is excited to shape the next generation of AI-assisted workflows for custom memory development. In this role, you will apply your expertise in IC design, layout, verification, simulation, and design automation to identify and deliver high-value solutions that improve engineering productivity, quality, and cycle time. This position offers the opportunity to build on a strong CAD foundation while growing into a broader AI-focused role over time. Responsibilities Design, develop, and deploy software, automation, and AI-assisted solutions that improve IC design workflows across layout, verification, simulation, and tape-out activities Develop and enhance AI-assisted tools, agents, and automation that improve engineering productivity and design team efficiency Collaborate with worldwide design, layout, verification, and CAD teams to identify high-impact use cases for automation and AI enablement Build a

Who we are At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to hundreds of thousands of businesses and empower millions of developers worldwide to craft personalized customer experiences. Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . Hiring and how we work We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings. . See yourself at Twilio Join the team as our next Machine Learning Engineer III in Twilio’s Customer Memory Team.. About the job In this role, you will build the foundational AI/ML capabilities that power intelligent engagement experiences for Twilio customers - letting any application, human or AI agent, or channel know who a customer is, what they have done, and how best to reach them. This role requires a builder and curious mindset, someone who can bridge the gap across theoretical research, production-grade experimentation and enterprise quality software. You will lead rapid research cycles to solve complex problems regarding contextual intelligence and large scale ML problems ensuring every interaction feels seamless and personalized. Responsibilities In this role, you’ll: Build out new functionality within a fast moving product seeing rapid adoption. Take a nebulous idea, design a rigorous experiment, and execute it within weeks. Conduct deep-dive research into

Leidos is looking for our next TS/SCI-cleared Elastic Search Engineer to join a high-energy team building and deploying a cutting-edge technology stack to support our client’s mission to centralize and standardize Tasking, Collection, Processing, Exploitation and Dissemination (TCPED) of Open Source Intelligence (OSINT) across the DoD and IC enterprise. We integrate off the shelf and newly development software to sustain and enhance the TCPED platform. We leverage cloud-based computing, artificial intelligence (Al), machine learning (ML) and cross-domain transfer systems to provide cutting edge data exploitation, enrichment, triage, and analytics capabilities to Defense and Intelligence Community members. DTP advances the state of the art in mission-focused big data analytics tools and micro-service development spanning the breadth of Agile sprints to multiyear research and development cycles. As an Elastic Search Engineer, you’ll be a member of our platform engineering team and help develop, deploy and maintain nosql databases as foundational elements of our microservice eco-system using a Kubernetes as foundational platform. You’ll also support the adoption of GitOps best practices across cross-functional engineering teams. In this fast-paced environment, you’ll collaborate closely with systems engineering, architecture, development, security, operations, and integrations teams. Work is conducted on-site at our client location in Bethesda, MD. Key Responsibilities Include: Deploy, triage, debug, and maintain production class databases like Elasticsearch and Redis Design and support database configuration management strategies across air-gapped network fabrics Partner with Systems Engineers to architect solutions for new capabilities Contribute to operational monitoring capabilities to provide proactive system notifications Contribute technical input to engineering documentati

We are looking for a passionate and skilled AI engineer who is responsible for designing and delivering complex generative AI solutions. This role requires the ability to work autonomously on challenging technical problems, provide mentorship to junior engineers and champion engineering best practices. Due to the nature of the projects and specific client security clearance, this role requires the successful candidate to be a Singapore Citizen or PR of Singapore. Job responsibilities Design, build and deploy GenAI applications using techniques such RAG, Agents, Multi Agent Systems etc., taking ideas from prototype to production. Work with both AI/ML engineers and software engineers to deliver reliable, scalable systems. Own key features or components, ensuring they are well-structured, efficient and easy to maintain. Make technical decisions and contribute to system design with attention to performance, cost and reliability. Collaborate with product managers, designers and data scientists to turn business needs into practical solutions. Share knowledge and mentor junior team members, helping them grow their technical skills. Review code and provide clear, constructive feedback to peers. Understand deployment options and trade offs across different cloud providers such as AWS, Azure, Google Cloud, etc. Understand optimization techniques to improve accuracy, performance and cost for GenAI applications. Job qualifications Technical Skills Strong software engineering fundamentals, including Python, CI/CD, testing, version control and clean code practices. Solid grasp of software design principles and ability to design and implement AI-powered components or workflows. Experience with at least one GenAI framework (e.g., LangChain, LlamaIndex, Semantic Kernel) and one agentic framework (e.g., PydanticAI, LangGraph, AutoGen2). Hands-on experience building and optimizing Retrieval-Augmented Generation (RAG) pipelines with vector databases (e.g., FAISS, Pinecone, Weaviate). F

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. Tenstorrent is looking for a mid- to senior-level Physical Design Engineer who will contribute to the physical design of high-performance chips for industry-leading AI/ML architectures, spanning implementation from synthesis through tapeout. You will partner with front-end and physical design engineers to optimize floorplanning, timing, power, performance, and area across multiple IPs. Along the way, you will build end-to-end ASIC expertise while learning from experienced engineers across the chip development process. This role is hybrid , based out of Austin, TX, Fort Collins, CO, or Santa Clara, CA . We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are An engineer excited to work on high-performance designs for industry-leading AI/ML architectures. A collaborative problem solver who enjoys working with experienced engineers across ASIC disciplines. Grounded in logic design fundamentals and gate- and transistor-level implementation. Curious about how early architectural and RTL decisions shape physical implementation and final chip quality. What We Need A BS, MS, or PhD in Electrical Engineering, Computer Engineering, Computer Science, or a relat

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. ## Key responsibilities - Design, build, and deploy AI agents and automation for CDR Sub-Towers and other AI Security initiatives - Follow direction set by Program Manager and Program Lead - Participate in peer review of other embed engineers' designs and receive review on your own - Coordinate with sub-tower leaders on their roadmap priorities - Contribute learnings, patterns, and reusable components back to the CDR AI Security team - Follow threat modeling and secure development practices set by the AI Security Program Lead --- ## Required qualifications - 5+ years of software engineering experience - Working knowledge of AI/ML product development — familiarity with LLMs, agents, RAG, or automation frameworks - Solid engineering fundamentals — auth, data handling, error handling, secure coding - Willingness to work closely with various CDR sub-towers — daily partnership, not remote arm's-length delivery - Comfort with peer review culture and shared standards - Domain-relevant curiosity — you'll be building for cybersecurity workflows, so willingness to learn CDR's sub-tower's domain deeply matters --- ## What success looks like in year 1 - You've deployed multiple production AI Security capabilities used by various sub-towers - You've contributed patterns, tools, or learnings back to the CDR AI Se

Tenstorrent is leading the industry on cutting-edge AI technology, revolutionizing performance expectations, ease of use, and cost efficiency. With AI redefining the computing paradigm, solutions must evolve to unify innovations in software models, compilers, platforms, networking, and semiconductors. Our diverse team of technologists have developed a high performance RISC-V CPU from scratch, and share a passion for AI and a deep desire to build the best AI platform possible. We value collaboration, curiosity, and a commitment to solving hard problems. We are growing our team and looking for contributors of all seniorities. We’re looking for a Field Sales Engineer who’s wired for AI/ML, fluent in real-world problem-solving, and excited to build with the people actually using what we make. You will collaborate closely with the sales team and enterprise customers, leveraging your deep technical knowledge in AI to drive the adoption of our products and solutions. This is a customer-facing role that requires both technical expertise and excellent communication skills to convey complex technical concepts to non-technical stakeholders. This role is remote based out of North America with preference near one of our main hubs Santa Clara, CA; Boston, MA; or Toronto,ON. We welcome candidates at various experience levels for this role. During the interview process, candidates will be assessed for the appropriate level, and offers will align with that level, which may differ from the one in this posting. Who You Are You’ve lived in the AI/ML trenches, whether as a field engineer, a solutions architect, or the one tapped in when things needed to “just work.” You speak both machine and human. Whether it’s a researcher or a skeptical executive, you know how to break things down and bring them to life. You’re fired up about generative models, LLMs, and the edge of what’s possible when software meets purpose-built silicon. Work directly with customers in pre-sales

At Dscout, we’re building the most flexible and powerful UX research platform on the market—trusted by the world’s top brands in finance (JP Morgan Chase, Intuit, Charles Schwab, PayPal), healthcare (Aya, Headspace), consumer goods (Keen, Verizon, Target, Northface), and tech (Google, Amazon, Facebook, Meta, Spotify, AirBnB). Our tools help teams deeply understand the humans behind their products, so they can build better ones. We are expanding our smart and driven team and would love for you to join us. AI native product is fundamentally different engineering problem than building deterministic software: the same input won't always produce the same output, and "working" means the agent behaves well across the full distribution of real world scenarios, not that it passes a fixed test suite. We're looking for an Applied AI Engineer with 2-5 years of experience building and shipping AI systems used by professionals at enterprise. You're comfortable working with modern LLM-based systems and agentic workflows, and you know how to turn powerful models into reliable product features. You have strong product judgment and think deeply about tradeoffs between LLM approaches and traditional ML when designing solutions. You care about evaluation, iteration speed, and making sure AI systems actually drive measurable business impact reliably . What you'll do Own the production improvement loop across agent behavior, customer and operator feedback, evaluation, experimentation, and verified business outcomes Instrument agent workflows so model interactions, tool use, decisions, failures, human edits, and downstream outcomes can be understood in context Define meaningful quality standards, representative evaluation datasets, regression coverage, and production monitoring. Investigate why agents underperform across context, knowledge, instructions, tools, routing, guardrails, or workflow design Design and ship targeted behavior improvements, including changes to prompting, cont

What you’ll do Act as the in-house electrical lead for Midjourney Medical: own the electrical architecture of the scanner and the technical direction for all board-level design. Own complex board design end-to-end: architecture, schematic capture, layout (high-speed digital, analog/mixed-signal, power), DFM/DFT, fabrication and assembly vendor management, bring-up, and revision control. Write firmware for embedded targets (MCU/SoC): drivers, real-time control loops, safety-relevant logic, bootloaders, and field update paths. Audit and update HDL (FPGA) code for high-throughput data acquisition, timing/synchronization, triggering, and pre-processing of ultrasound and sensor data streams. Define electrical interfaces and data contracts with software, recon/ML and mechanical teams: timing budgets, clocking/sync, signal integrity, connectors/harnessing, and failure modes. Establish electrical engineering rigor: design reviews, schematic/layout review checklists, bring-up procedures, test fixtures, and documentation suitable for a regulated medical device program (DHF, traceability, change control). Mentor and grow the electrical function; select and manage external design partners where leverage is high. What we’re looking for Deep experience designing complex boards from blank page to stable revision, including high-speed digital and analog/mixed-signal domains. Strong schematic and layout skills (Altium/KiCad or equivalent) with real signal integrity, power integrity, grounding, and EMI/EMC instincts. Solid embedded firmware background in C/C++ (and Python for tooling): peripherals, DMA, interrupts, real-time constraints, and debugging on hardware. Practical HDL experience (VHDL/Verilog/SystemVerilog) for data acquisition, timing, and streaming interfaces. Track record of owning bring-up and debug on real hardware: scopes, logic analyzers, and disciplined root-cause analysis. Technical leadership: clear trade-offs, strong written documentation, and the ability to set