Ai Ml Infra Systems Engineer Jobs

About the Role At Sigma, we’re not just adding AI—we’re building the future of how people work with data. Our platform already lets users explore billions of rows of data in seconds with a spreadsheet-like interface, analyze and present their data in workbooks, and build data apps and workflows. Now we’re pushing further, applying AI to reshape how people build in Sigma, discover insights, and make smarter decisions—fast. You can learn more about our vision for AI/ML at Sigma in our blog post . That’s where you come in. As an AI/ML PhD Intern , you’ll join a growing team focused on building the AI foundation that will power Sigma for the future. Your work will become an integral part of the workflow for the thousands of enterprises that run on Sigma. We're looking for PhD students that are passionate about the intersection of AI, business, and data. What You’ll Do Conduct original AI/ML research in search, recommendations, natural language processing, agentic workflows and more Prototype and productionize AI systems that feel intuitive but do a lot under the hood Tackle novel UX problems at the intersection of AI, analytics, and data apps Contribute to the development of scalable AI/ML infrastructure for experimentation, training, and evaluation of large-scale models. What You Bring Current PhD student studying AI/ML at a U.S. accredited university Deep understanding of machine learning, including deep learning algorithms, model architectures and optimization Baseline understanding of building and deploying production-grade AI/ML systems Knowledge of the full ML lifecycle: data curation, training, deployment, monitoring Desire to bridge research and application—bringing new AI ideas from concept to impactful deployment. Bonus Points (or skills you’ll build here) You've built agents that can plan, reason, and use tools You’ve fine-tuned or trained foundation models (language or multimodal) for novel domains You know your way around cloud infrastru

AI/ML Solution Architect Education & Assessment Platforms About Pratham International Pratham International is a US 501(c)(3) established to support learning innovations for children and youth in contexts across the globe. We enable the adaptation and spread of proven and scalable education solutions pioneered in India by Pratham Education Foundation to contexts across the global south through programming and technical assistance tailored to local realities. Today, Pratham innovations reach millions of children annually through partnerships across ~30 countries. Through the Pratham Shah PraDigi Innovation Centre (PraDigi), Pratham International also seeks to create technology innovations for low-resource communities, and support models aimed at learning for school, work, and life for children and youth. We work on several cutting-edge projects in the domain of Generative AI, Automatic Speech Recognition, and Natural Language Processing. The team’s innovative technology products include the PadhAI: Reading Assessment App, which uses advanced speech recognition to evaluate children’s reading fluency in 8 Indian languages and 6 global languages; Anytime Testing Machine (ATM), an AI-enabled question generation and grading system that allows learners to be assessed on any topic, anytime; and a suite of AI-powered chatbots designed for diverse learning contexts: from early childhood care, to youth employment readiness, and OCR-based analysis tools that digitize and assess student work at scale. At Pratham International, we build for the long term. Whether it’s ensuring products are truly accessible across rural India and the global south through languages, building datasets to ensure context and accuracy for products, or gathering feedback from the field. Backed by partners like Google.org, Anthropic, and the Gates Foundation, we are committed to building digital public goods that ensure every child is in school and learning well. Role Overview About the work We desig

For over 20 years, Smartsheet has empowered teams to manage work seamlessly and scale solutions smarter. Now, in our most ambitious chapter yet, we are uniting human teams with AI agents. By orchestrating the work agents do best, automating manual tasks and uncovering insights at scale, we create the space for people to focus on what truly matters: judgment, creativity, and big thinking. That is magic at work, and it’s what we show up for every day. Job Description/ Responsibilities: Designing, developing and maintaining stable and reliable AI/ML Ops platforms / pipelines Minimum experience of 4-6 Years required in AI ML Ops Model Deployment: Package and deploy AI/ML services to production, ensuring they are reproducible and interpretable CI/CD Pipeline Development: Design and implement automated CI/CD (Continuous Integration/Continuous Deployment) pipelines to accelerate model deployment using tools Infrastructure Management: Provision and optimize infrastructure for training and serving, utilizing Docker, Kubernetes, or serverless platforms Monitoring & Observability : Implement post-deployment monitoring for model performance, data drift, and latency using tools. Experience in Monte Carlo is preferable Automation: Automate retraining and data pipeline workflows to ensure models stay accurate over time. Manage the deployment of foundation models, fine-tuning workflows, and Retrieval-Augmented Generation (RAG) stacks (Vector DBs, Knowledge Graph. Experience with AWS Bedrock is preferable Resource Optimization: Manage GPU/CPU utilization to minimize cloud costs while maintaining low-latency inference for users Collaboration: Work closely with data scientists, data engineers, and software engineers to bridge the gap between model development and production. Version Control & Governance: Manage versioning for data, code, and models using tools like MLflow. Security & Compliance: Implementing data security measures, ensuring compliance with data governance

On-site | Vancouver Office – 564 Beatty St About EviSmart EviSmart builds the automation layer that dental laboratories run on. A dental lab is a manufacturing operation. A case arrives from a dentist — a 3D scan of a patient's mouth and a prescription — and leaves as a crown, bridge, denture or night guard. In between sit a dozen manual steps: monitoring scanner portals, retyping cases into lab software, checking scan quality, interpreting handwritten prescriptions, designing the restoration. We automate that pipeline. Our software connects to 15 intraoral scanner portals and more than five lab management systems, pulls cases the moment they arrive, reads the prescription, maps it into the lab's own product catalogue, checks the scan, and routes it to design. We serve roughly 6,000 customers across 28 countries from offices in Vancouver, Manila, Seoul and Shenzhen. The automation works. It does not yet work well enough, consistently enough, to run unattended — and closing that gap is the highest-leverage technical problem in the company. What you'll do Establish measurement. Build per-model, per-customer, per-category accuracy reporting that Product and Sales can act on. Nothing else you do matters until this exists. Build the correction flywheel. Capture the quality-control corrections our customers already make, turn them into structured, versioned training data, and close the loop with human review where confidence is low. Standardize the squads. One deployment path, one evaluation harness, one model and dataset registry across restoration design, scan quality, prescription extraction and agents. Solve multi-tenant model behaviour. Thousands of customer-specific product codes, prescription conventions and unwritten preferences sitting over a shared model base — without building a bespoke model per customer. Take inference to production scale. Move workloads from on-premise to cloud with understood cost per inference and real concurrency headroom. •

Sapience AI is the collective intelligence platform for professional communities. We sit above the CRMs, AMS platforms, and knowledge bases that organizations already run, and we turn the expertise scattered across them into something every member can search, act on, and share. The intelligence a community needs is already inside it. Most organizations just cannot reach it. Knowledge lives in silos, in legacy systems, in the heads of a few experts, and in fragmented records no one can connect. We change that. Our work is grounded in four commitments: technology elevates people and never replaces them, the best expertise is already inside the community, everything is built on trust, and every deployment is purpose-driven for the organization it serves. Let’s achieve more, together. Where this role sits This role builds the structured knowledge that collective intelligence reasons over. You own the KO (knowledge object) graph: the layer that turns a community’s scattered expertise into connected, queryable knowledge the COGENT architecture can use. You work where messy real-world data becomes trustworthy structure: ingesting, resolving, connecting, and modeling knowledge so reasoning has something solid to stand on. You partner closely with neuro-symbolic AI and applied AI, and you are the reason the platform can answer questions that span a community’s knowledge instead of isolated documents. Why this role exists Language models are fluent, but fluency is not knowledge. To reason over a community’s expertise with rigor, the platform needs that expertise structured, connected, and trustworthy, not just retrieved as text. Building a knowledge graph from real, fragmented sources is hard: entities to resolve, relationships to infer, quality to enforce, and provenance to preserve. The graph is only as good as the engineering behind it. The AI/ML Data and KO Graph Engineer builds that foundation. You turn scattered knowledge into a graph the COGENT architecture can reason

About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . Your role As a Sr. AI Engineer: Systems, you’ll serve as an embedded senior back-end engineer on our Speech Team, owning the production systems that turn speech models and third-party capabilities into reliable, scalable experiences for Dialpad’s AI voice agents. You’ll work at the intersection of speech, ML infrastructure, and

Come build what the market has been missing. Octaura is a technology company transforming how some of the world’s largest, least digitized markets operate. In loans and CLOs, trillions of dollars still move through phones, emails, and PDFs because the right infrastructure hasn’t existed — until now. We’re applying AI, real-time data, and modern software design to asset classes long overlooked by fintech. Our platforms turn fragmented information into intelligence, manual workflows into automation, and legacy conventions into scalable market infrastructure. You’ll join a high-impact, collaborative team building the systems these markets need to become more transparent, efficient, and connected. The Role An AI Engineer at Octaura, is a software professional who develops and implements AI-powered applications by integrating trained machine learning models, APIs, and data pipelines into functional software products. You will design, build, deploy, and maintain applied machine learning systems that power critical products and workflows across our platform. This role focuses on taking AI solutions from concept through production—working with large, complex datasets and ensuring models are reliable, explainable, and performant in real-world financial environments. You’ll partner closely with product managers, software engineers, and data teams to solve meaningful business problems, improve market efficiency, and introduce AI responsibly into mission-critical systems. Depending on experience, you may take full ownership of complex AI initiatives and help shape Octaura’s ML architecture and best practices. This role is based out of our New York City office (5 Penn Plaza), with a hybrid schedule of four days in the office (Monday–Thursday) and one day remote (Friday). Key Responsibilities Design, build, and maintain production-grade backend services that power AI/ML capabilities, using Java, Spring Boot, Kafka, Redis, PostgreSQL, an

AI/ML Dev - Chatbots • 8+ years of experience in Data/AI Projects • Understanding of end-to-end architecture for Generative AI solutions aligned with business goals. • Experience in Azure OpenAI integration (GPT models, embeddings) with prompt engineering and model tuning. • Programming experience in Python for AI project is a must • Designs scalable RAG systems using Azure AI Search, vector databases, and secure data pipelines. • Knowledge of MLOps and CI/CD workflows using Azure DevOps and automated testing frameworks. • Establishes Python coding standards, reviews code, and mentors development teams. • Knowledge of deployment and governance of AI applications across Azure infrastructure. • Work with cross function teams (IT/ Non IT) to help the development teams build the solutions faster and more efficiently.

PagerDuty, Inc. (NYSE: PD) is the global leader in AI-first digital operations. By automatically detecting, diagnosing, and remediating issues, the PagerDuty Platform orchestrates AI agents and automated workflows with context from over 750 integrations. Trusted by approximately two-thirds of the Fortune 100 and nearly half of the Fortune 500, PagerDuty is the industry standard for organizations scaling resilient, autonomous operations. Notable customers include Chipotle, Cloudflare, Docusign, Fox, Nvidia, Salesforce, Spotify, Zoom and more. We are growing rapidly and hiring top talent with leading AI skills across engineering, sales, product, marketing, and beyond as we build the leading digital operations platform. About the role PagerDuty’s Operations Cloud runs on a platform that ingests billions of signals and turns them into real-time action for thousands of customers. We’re looking for an early-career AI/ML Engineer who is excited to grow at the intersection of two disciplines: large-scale distributed systems and machine learning. In this role you will help build and ship AI systems that run in production at PagerDuty’s scale — powering Incident Management AI Agents, event intelligence, and the LLM-powered capabilities embedded across our platform. You’ll work alongside senior engineers on real production problems, learning how AI features go from a prototype to something that serves reliably at scale. We are looking for a candidate who is genuinely excited about building with modern AI — LLMs, agents, and retrieval — eager to learn how resilient, high-throughput systems are built, and motivated to grow into an engineer who is strong in both. What you’ll do Contribute to AI-powered features — LLM agents, retrieval, and event intelligence — that operate on high-volume, real-time data, with support and guidance from senior engineers. Help build and maintain the systems behind them — prompt and agent orchestration, retrieval pipelines, tool/API integratio

NK Securities Research is a leading financial firm that leverages cutting-edge technology, data-driven research, and sophisticated algorithms to trade financial markets. Founded in 2011, we have built deep expertise in high-frequency trading across different asset classes. We are a fast-growing organization with a strong research and technology culture. The firm’s lean and meritocratic structure enables individuals to work closely with experienced researchers, traders, and engineers, while taking ownership of high-impact problems from an early stage. Role Overview We are looking for an AI/ML Researcher to join our central AI/ML research team in India. This is a research-intensive role suited for individuals who enjoy mathematical problem-solving, experimentation, and working with complex, noisy, high-dimensional datasets. The role will involve close collaboration with quantitative researchers, traders, engineers, and business stakeholders to identify areas where AI/ML can create meaningful value across the firm. The ideal candidate should be comfortable working on open-ended research problems, converting ideas into structured experiments, and building models that can be evaluated rigorously in real-world settings. Key Responsibilities As an AI/ML Researcher, you will: Work on our GPU cluster to research and understand the fine-grained behavior of large neural networks and LLM training. Fine-tune existing open-source models and build benchmarks to evaluate their performance. Explore and analyze large-scale financial market datasets. Build ML and statistical models for pattern discovery, prediction, and signal generation. Work on short-horizon, noisy, and non-stationary market data. Conduct feature engineering, model validation, and performance evaluation. Study pricing, market microstructure, and execution-related research problems. Convert research ideas into structured experiments with measurable outcomes. Collaborate with quantitative researchers, trad

Want to be a bswifter? At bswift we’ve been transforming benefits administration since 1996, making it simpler, smarter, and more human. Our state-of-the-art, cloud-based technology and services empower employees to understand, manage, and love their benefits. From downtown Chicago, and remotely across the country, we serve thousands of companies and millions of people nationwide, reducing administrative burdens and freeing HR teams to focus on creating thriving, people-first workplaces. We’re looking for motivated and goal-driven individuals who share our passion for delivering excellence and creating solutions that make a difference. The reward is a fun, flexible and creative environment with ample opportunity for professional and personal growth. If you love the bswift values of pursue excellence, embrace accountability, deliver superior service, and be a great place to work, we want to hear from you! About the Role We are looking for an AI Engineer II to design, build, and deploy cutting-edge generative AI applications , including agentic workflows and intelligent chat experiences , that transform how employees interact with their benefits. This role goes beyond individual contribution—you will own complex AI features end-to-end , influence architecture decisions around LLMs and agent systems , and mentor junior engineers . You will play a key role in bringing secure, scalable, and high-performance AI solutions to production using AWS cloud technologies. You will collaborate closely with software engineers, architects, product managers, and cross-functional teams to deliver seamless and impactful user experiences Key Responsibilities 1. Solution Design & Development Lead the design and development of scalable, secure, and high-performance applications . Architect robust backend systems and integrate them with frontend applications and third-party services. Drive technical decisions and participate in design reviews alongside senio

About the role Chime's Data Science & Machine Learning team builds the models, services, and platforms behind how millions of members manage and grow their financial lives. We're hiring AI/ML Engineers across several teams, Trust & Safety, Lending, Growth, and Foundation Models, and you'll be matched with the team where your background, experience and interests fit best. In this role, you'll build and deploy machine learning systems on some of the richest transactional and behavioral data in fintech, turning it into decisions that protect members from fraud, expand access to credit, and power the personalized experiences and marketing that help millions of members get more out of products like MyPay, Instant Loans, and SpotMe — along with the foundational models the rest of our teams build on. This is a highly applied role: you'll own problems end to end, from framing the question through to a model running in production and moving a metric that matters. In this role, you can expect to Build, train, and deploy deep learning and classical ML models on large-scale financial, transactional, and behavioral datasets Take models from problem framing through to production — training, evaluation, deployment, monitoring, and iteration — and stay accountable for how they behave once they're live Design and improve the systems around the model: feature pipelines, batch and real-time inference, monitoring, and retraining Partner with Product, Engineering, Analytics, and Risk to turn ambiguous business problems into ML solutions, and to make sure the solution is the right one Connect model performance to member outcomes and business metrics, and use experimentation to prove impact Contribute to the shared ML platform, tooling, and standards that the rest of the team builds on Help identify where AI/ML creates measurable impact for members — and where a simpler answer is the better one To thrive in this role, you have Experience building and deploying deep learning models

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 an Physical Design Engineer to lead cross-functional efforts to solve complex physical design challenges and develop end-to-end RTL-to-GDS methodologies across advanced nodes, with a strong focus on PPA and runtime improvements. The engineer will architect, integrate, and deploy AI/ML-driven solutions into production physical design flows, creating custom CAD tools and partnering with internal teams and EDA vendors to drive next-generation, ML-enabled capabilities. This role is hybrid, based out of Santa Clara, CA or Austin, TX 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 BS in Electrical or Computer Engineering (or equivalent experience) with 5+ years in Physical Design CAD methodology at advanced nodes. Proven track record improving PPA and/or runtime on high-performance, low-power taped-out designs. Hands-on with industry-standard EDA tools (e.g., Fusion Compiler) across synthesis, P&R, STA, signoff, and hierarchical flows. Strong Python/Tcl and data skills, with interest or experience in ML frameworks (PyTorch, TensorFlow), and the ability to drive complex projects independent

AI/ML – Investment Services A Career with Point72's AI/ML – Investment Services Team The AI/ML – Investment Services team at Point72 spearheads the development of cutting-edge AI solutions that seek to transform our business processes and enhance enterprise intelligence. The team aims to bridge the gap between business challenges and technological innovation, collaborating with stakeholders across the firm and leveraging expertise in generative AI, data engineering, and machine learning. WHAT YOU'LL DO Build and scale core backend services and platforms that power generative AI applications and data infrastructure used across the firm’s investment workflows Design and implement high-throughput, low-latency data pipelines to ingest, normalize, and serve both structured and unstructured data Develop robust APIs and microservices to support model inference, feature serving, and downstream applications Integrate generative AI tools and model-serving workflows into production, including embedding stores, retrieval components, and fine-tuning pipelines Optimize system performance, cost, and reliability through profiling, capacity planning, and architectural improvements Implement automated testing, continuous delivery pipelines, monitoring, and incident response practices to maintain production health Partner with data scientists, AI engineers, product owners, and operations to translate models and prototypes into scalable, production-grade solutions Mentor engineers, lead code reviews, and establish engineering best practices for maintainability, security, and observability Own end-to-end delivery, operational runbooks, and metrics-driven measurement of feature impact and system reliability WHAT'S REQUIRED Bachelor’s degree in computer science, software engineering, or a related technical field Minimum 5+ years of professional experience building backend systems and production services Demonstrated experience designing and operating large-scale data engineering pipelines

AI/ML Engineer/Architect — Boise, ID - Main Site. Apply via Workday.