Machine Learning Engineer Remote Jobs in Iowa (US)
This page tracks remote machine learning engineer openings that are location-eligible for Iowa.
This page tracks remote machine learning engineer openings that are location-eligible for Iowa.
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Role Description A well-funded seed-stage startup building the next generation of autonomous trading technology. You are building the intelligence layer on top of a purpose-built execution system for AI agents operating with real capital around the clock. What You'll Own - Learning System & RL Loop (~70%): - Design and implement the pipeline that connects live trade outcomes back to strategy improvement — signal quality, position sizing, timing, risk parameters. - Build the evaluation framework that separates genuine predictive signal from noise across agents, market conditions, and configurations. - Automate the strategy generation and testing cycle — the system should explore new configurations, validate them against real fleet data, and surface deployment candidates. - Detect regime shifts in market conditions and adapt fleet behavior accordingly. - Decompose every trade into its component drivers — signal quality, execution efficiency, exit timing — and wire those attributions back into strategy design. - Manage fleet-level coordination: concentration risk, capital allocation, and the exploration vs. exploitation balance. - Build the telemetry and data capture layer that makes all of the above possible. - Model & Inference Infrastructure (~30%): - Own the build-vs-buy decision on model hosting — evaluate proxied external APIs versus fine-tuned models on owned infrastructure and execute the chosen path. - Determine whether domain-specific training on trading data meaningfully outperforms prompted general-purpose models — then build the pipeline to act on that answer. - Optimize inference for the specific demands of a large autonomous agent fleet: concurrent agents, structured outputs, cost efficiency at scale. - Build the agent telemetry layer capturing every decision, signal score, and evaluation across the fleet. Qualifications - A production closed-loop system — model outputs drove real-world actions, outcomes were measured, and that feedback automatically improved the next decision. - Practical RL or online learning experience — you understand the challenges of learning from real-world feedback rather than static datasets. - Full-stack ML ownership — you build the pipeline, deploy the model, and own the outcome; Python primary, comfortable with Go or TypeScript in production services. - High-stakes sequential decision-making domain experience — finance preferred but not required; robotics, autonomous vehicles, game AI, ad bidding, and supply chain all transfer. Nice to Have - LLM fine-tuning and open-source model serving in production (vLLM, TGI, PEFT/LoRA). - Multi-agent system design. - Financial ML — signal generation, execution optimization, portfolio construction. - Onchain or DeFi experience. Interview Process - Fast — target first call to offer within two weeks. - Intro call with founders (60 min) — fit, motivation, your closed-loop experience. - Technical deep-dive (60 min) — open-ended system design, no right answer, evaluating how you think. - Paid trial project (1 week, part-time) if needed — real problem, compensated.
The CES Family of Companies is a collection of strong brands and businesses providing food equipment, supplies, service.
• Design and implement AI/GenAI features across applications and SDLC workflows • Build AI solutions using platforms like Azure AI Foundry and LLM APIs • Develop agent-based workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel • Implement RAG-based solutions and prompt engineering strategies • Leverage GitHub Copilot for AI-assisted development and productivity • Build full-stack applications using Python, JavaScript/TypeScript, and/or C# (.NET) • Develop APIs, backend services, and integrate with databases (SQL/NoSQL) • Ensure application quality through testing, monitoring, and observability • Collaborate with cross-functional teams (product, UX, data science) • Troubleshoot and optimize AI models, pipelines, and integrations
Role Description Throughput. Latency. KV cache utilization. Move those three numbers in the right direction, and two things happen: customers get faster, cheaper inference, and our margins improve. That's the entire thesis of this role. Every kernel you tune, every quantization scheme you ship, every scheduler tweak you land shows up directly in a customer's p99 and on our P&L. This is a high-impact seat. It is also a high-autonomy seat as you'll be given the room to lead the technical direction of inference optimization at Kimchi, not execute someone else's roadmap. The problem: running LLMs in production is a moving target. The "right" model and serving configuration for a workload depend on: - Traffic shape - Sequence-length distribution - Batch dynamics - GPU SKU - Memory bandwidth - Quantization tolerance - A dozen other variables that shift week to week Most teams pick a model once, over-provision GPUs, and absorb the cost. Kimchi is the system that makes that decision automatically - continuously matching workloads to the most cost-efficient, best-performing LLM and serving configuration on a customer's infrastructure. We're building the optimization layer between the model and the hardware, and we need engineers who understand both sides deeply. Qualifications - 5+ years building real ML systems, with a portfolio that shows depth in inference or training infrastructure (not just model training notebooks). - Strong Python - production services, not scripts. - Hands-on experience with at least one of vLLM, SGLang, or TensorRT-LLM, and a working mental model of why an inference engine performs the way it does on a given GPU. - Fluency with quantization tradeoffs - you've measured quality regressions, not just compression ratios. - Comfort with distributed systems: collective communication, sharding strategies, and the practical failure modes of multi-GPU and multi-node setups. - A bias toward measurement. You instrument before you optimize, and you can tell the difference between a real win and a benchmark artifact. - Self-direction. This role comes with a wide mandate; you should be excited by that, not unsettled by it. Requirements - Push throughput. Continuous batching, speculative decoding, chunked prefill, kernel-level tuning across vLLM, SGLang, and TensorRT-LLM. Find the ceiling on each GPU SKU, then raise it. - Cut latency. Attack TTFT and TPOT separately. Profile, identify the actual bottleneck (compute, memory bandwidth, scheduling, networking), and fix it - not the bottleneck you assumed. - Get more out of the KV cache. Paged attention, prefix caching, eviction policies, cache reuse across requests, quantized KV. This is where a lot of the unrealized throughput lives, and it's an area you'll own. - Quantize without regressing quality. INT8, INT4, FP8 across weights, activations, and KV. Empirical work: measure quality on real workloads, not just perplexity benchmarks. - Shrink cold starts and memory footprint. Faster init, smarter weight loading, tighter memory accounting - the difference between a model that scales and one that doesn't. - Scale across nodes. Distributed inference topologies, network-aware placement, checkpointing strategies that don't bottleneck on storage or interconnect. - Set the technical direction. Decide what we benchmark, what we adopt, and what we build ourselves. Bring the team along with strong writeups and reproducible experiments. Benefits - Competitive salary (depending on the level of experience). - Enjoy a flexible, remote-first global environment. - Collaborate with a global team of cloud experts and innovators, passionate about pushing the boundaries of Kubernetes technology. - Equity options. - Get quick feedback with a fast-paced workflow. Most feature projects are completed in 1 to 4 weeks. - Spend 10% of your work time on personal projects or self-improvement. - Learning budget for professional and personal development - including access to international conferences and courses that elevate your skills. - Annual hackathon to spark new ideas and strengthen team bonds. - Team-building budget and company events to connect with your colleagues. - Equipment budget to ensure you have everything you need. - Extra days off to help maintain a healthy work-life balance. Hiring process - Screening call with Recruiter - Hiring Manager interview - Technical interview (system design) - Live coding - Culture Check interview with an executive As part of our standard hiring process, we would like to inform you that a background check may be conducted at the final stage of recruitment through our third-party provider, Checkr. Please note that Cast AI does not provide any form of visa sponsorship/work permit.
Top world’s largest social discovery company uniting 70+ brands with 500M+ users
• Conducting experiments with LLMs: Explore and analyze the effectiveness of different architectures and techniques (SFT, RLHF, Adapters, etc.) to enhance the capabilities of AI models. • Developing and implementing evaluation methodologies: Implement and maintain robust frameworks to assess the performance, accuracy, and user satisfaction of AI bots, including offline and online metrics. • Optimizing models for inference: Improve the efficiency and speed of AI models during inference to ensure they meet the performance and scalability requirements for production environments. • Collaborating with cross-functional teams: Work closely with data scientists, software engineers, and product managers to integrate AI solutions into the overall product pipeline.
Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.
Role Description We are building the first super app to manage car ownership—an industry where the experience is stuck in the 90s. Lead a strategic area leveraging LLMs, agents, and internal APIs to automate a fragmented, $2T market. Work with partners at OpenAI to integrate Jerry.ai services directly into the ChatGPT App and pioneer new model capabilities. At Jerry.ai, we are moving past fragmented, time-consuming processes to create a seamless, automated platform. You will sit at the intersection of product, engineering, and applied AI as you build and scale a sophisticated system that already automates >70% of inbound sales and service requests (over 50k chats per month). Your role will include shaping how modern LLM systems, human-in-the-loop feedback, and computer-use agents redefine an entire industry. How You Will Make an Impact: - Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout. - Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy. - Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards. - Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation. - Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation. Qualifications - 3+ years of experience in management consulting or technical product management at a fast-paced startup. - Proven interest in modern LLM systems. - Ability to navigate technical tradeoffs and lead by example when implementing AI platform standards. - A track record of taking complex, strategic ideas and turning them into scalable, production-grade products. Requirements - Intrinsically Motivated Technologist: You live and breathe AI. You read the release notes when a new model drops and you’ve already built your own custom workflows. - Systems Thinker: You are comfortable diving into technical conversations about API design and system architecture, translating complex concepts for any audience. - Optimistic Problem-Solver: You are a "how can we" thinker who seeks constant improvement and thrives on owning high-impact metrics. - Data-Driven with Conviction: You are familiar with SQL and comfortable diving into the data to answer your own questions and validate hypotheses. Benefits - Comprehensive benefits package including health, dental, and vision coverage. - Paid time off and paid parental leave. - 401(K) plan with employer matching. - Wellness benefits. - Equity opportunities may also be part of your total rewards package.
Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. We spend every day innovating and improving our AI-powered app to provide the best possible experience for our customers. We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. We have more than 5 million customers — and we’re just getting started. Founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.
Role Description We are building the first super app to manage car ownership—an industry where the experience is stuck in the 90s. Lead a strategic area leveraging LLMs, agents, and internal APIs to automate a fragmented, $2T market. Work with partners at OpenAI to integrate Jerry.ai services directly into the ChatGPT App and pioneer new model capabilities. At Jerry.ai, we are moving past fragmented, time-consuming processes to create a seamless, automated platform. You will sit at the intersection of product, engineering, and applied AI as you build and scale a sophisticated system that already automates >70% of inbound sales and service requests (over 50k chats per month). Your role will include shaping how modern LLM systems, human-in-the-loop feedback, and computer-use agents redefine an entire industry. How You Will Make an Impact: - Lead end-to-end development for our AI platform and customer experiences, from initial roadmap to rollout. - Partner with engineers to design prompt strategies, evaluation frameworks, and guardrails—balancing latency, cost, and accuracy. - Serve as the technical translator between engineering and the broader organization, establishing AI best practices and platform standards. - Drive systematic improvement in answer quality, customer satisfaction, and automation rates through rigorous experimentation. - Work with partners at OpenAI to evaluate and deploy the next generation of voice models and workflow automation. Qualifications - 4+ years of experience in management consulting or technical product management at a fast-paced startup. - Proven interest in modern LLM systems. - Ability to navigate technical tradeoffs and lead by example when implementing AI platform standards. - A track record of taking complex, strategic ideas and turning them into scalable, production-grade products. Requirements - Intrinsically Motivated Technologist: You live and breathe AI. You read the release notes when a new model drops and you’ve already built your own custom workflows. - Systems Thinker: You are comfortable diving into technical conversations about API design and system architecture, translating complex concepts for any audience. - Optimistic Problem-Solver: You are a "how can we" thinker who seeks constant improvement and thrives on owning high-impact metrics. - Data-Driven with Conviction: You are familiar with SQL and comfortable diving into the data to answer your own questions and validate hypotheses. Benefits - Comprehensive benefits package including health, dental, and vision coverage. - Paid time off and paid parental leave. - 401(K) plan with employer matching. - Wellness benefits. - Equity opportunities may also be part of your total rewards package. Company Description Jerry.ai is America’s first and only super app to radically simplify car ownership. We are redefining how people manage owning a car, one of their most expensive and time-consuming assets. - Backed by artificial intelligence and machine learning, Jerry.ai simplifies and automates owning and maintaining a car while providing personalized services for all car owners' needs. - We are the #1 rated and most downloaded app in our category with a 4.7 star rating in the App Store. - We have more than 5 million customers — and we’re just getting started. - Founded in 2017 by serial entrepreneurs and has raised more than $240 million in financing. Join our team and work with passionate, curious and egoless people who love solving real-world problems. Help us build a revolutionary product that’s disrupting a massive market.
Airbnb is a community based on connection and belonging.
• Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale. • Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents. • Design methods for plan induction, value estimation, and contingency modeling within intelligent agents. • Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems. • Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers. • Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates. • Build and evolve stateful, dynamic models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol grounding. • Set direction for planning/reasoning infrastructure within the AI/ML platform strategy.
Airbnb is a community based on connection and belonging.
• Fine-tune state-of-the-art LLMs for diverse use cases while optimizing models. • Partner with product managers, software engineers, data scientists and operation teams. • Brainstorm, design and develop AI products like AI Assistant and Autonomous agent. • Work with large scale structured and unstructured data to continuously improve foundation models. • Create a multi-year tech roadmap for the team. • Continuously evaluate foundational models for enhanced performance and efficiency. • Hands-on prototype, develop and productionize LLM models and pipelines. • Drive AI architectural decisions and contribute to ML platform architecture.
Turnitin is a global software development company in the education sector working to ensure the integrity of education and research, and to meaningfully improve learning outcomes.
Role Description Turnitin is a recognized innovator in the global education space. For more than 20 years, Turnitin has partnered with educational institutions to promote honesty, consistency, and fairness across all subject areas and assessment types. Over 16,000 academic institutions, publishers, and corporations use our products and services. At Turnitin, working remotely is our default. We respect local cultures, embrace diversity, and we respect personal choice. Our diverse community of colleagues is unified by a shared desire to make a difference in education. Our remote-first culture allows for every employee to get the same access to learning and career opportunities, and it enables us to think differently about where and how we recruit talent from all kinds of diverse backgrounds. Machine Learning is integral to the continued success of our company. Our product roadmap is exciting and ambitious. You will join a global team of curious, helpful, and independent scientists and engineers, united by a commitment to deliver cutting-edge, well-engineered Machine Learning systems. You will work closely with product and engineering teams across Turnitin to integrate Machine Learning into a broad suite of learning, teaching, and integrity products. Your contributions will have global reach and scale. Billions of papers have been submitted to the Turnitin platform, and hundreds of millions of answers have been graded on the Gradescope and Examsoft platforms. Machine Learning powers our AI Writing detection system, gives automated feedback on student writing, investigates authorship of student writing, revolutionizes the creation and grading of assessments, and plays a critical role in many back-end processes. Responsibilities - Work with subject matter experts and product owners to determine what questions should be asked and what questions can be answered. - Work with subject matter experts to curate, generate, and annotate data, and create optimal datasets following responsible data collection and model maintenance practices. - Answer questions and make trainable datasets from raw data, using efficient SQL queries and scripting languages, visualizing when necessary. - Develop and tune Machine Learning models, following best practices to select datasets, architectures, and model parameters. - Utilize, adopt, and fine-tune Language Models, including third-party LLMs (through prompt engineering and orchestration) and locally hosted LMs. - Stay current in the field - read research papers, experiment with new architectures and LLMs, and share your findings. - Optimize models for scaled production usage. - Communicate insights, as well as the behavior and limitations of models, to peers, subject matter experts, and product owners. - Write clean, efficient, and modular code, with automated tests and appropriate documentation. - Stay up to date with technology, make good technological choices, and be able to explain them to the organization. Qualifications - Experience working with text data to build Deep Learning and ML models, both supervised and unsupervised. Experience with deep learning in other modalities such as vision and speech would be a strong bonus. - A strong understanding of the math and theory behind machine learning and deep learning. - Software engineering background with at least 8 years of experience (we use Python, SQL, Unix-based systems, git, and github for collaboration and review). - Machine / Deep Learning development skills, including experiment tracking (we use AWS SageMaker, Hugging Face, transformers, PyTorch, scikit-learn, Jupyter, Weights & Biases). - An understanding of Language Models, using and training / fine-tuning and a familiarity with industry-standard LM families. - Master's degree or PhD in Computer Science, Electrical Engineering, AI, Machine Learning, applied math or related field, with relevant industry experience, or outstanding previous achievements in this role. - Excellent communication and teamwork skills. - Fluent in written and spoken English. Requirements - Familiarity in coding for at-scale production, ranging from best practices to building back-end API services or stand-alone libraries. - Essential dev-ops skills (we use Docker, AWS EC2/Batch/Lambda). - Familiarity in building front-ends (LLMs or more standard React, Javascript, Flask) for simple demos, POCs and prototypes. - Experience with advanced prompting, fine-tuning or training an LLM, open-source or cloud, using industry accepted platforms (such as mosaic.ai or stochastic.ai). - Showcase previous work (e.g. via a website, presentation, open source code). Benefits - Remote First Culture - Health Care Coverage* - Education Reimbursement* - Competitive Paid Time Off - 4 Self-Care Days per year - National Holidays* - 2 Founder Days + Juneteenth Observed - Paid Volunteer Time* - Charitable contribution match* - Monthly Wellness or Home Office Reimbursement* - Access to Modern Health (mental health platform) - Parental Leave* - Retirement Plan with match/contribution* Company Description When you join Turnitin, you'll be welcomed into a company that is a recognized innovator in the global education space. For over 25 years, Turnitin has partnered with educational institutions to promote honesty, consistency, and fairness across all subject areas and assessment types. Over 21,000 academic institutions, publishers, and corporations use our services: Feedback Studio, Originality, Gradescope, ExamSoft, Similarity, and iThenticate. Turnitin is a global organization with team members in over 35 countries including the United States, Mexico, United Kingdom, Australia, Japan, India, and the Philippines. Turnitin, LLC is an equal opportunity employer- vets/disabled.
Work for a Fortune 500 company that rewards performance, invests in your growth, and provides a launchpad for a high-earning remote sales career. This isn’t just a job — it’s your path to leadership, income, and long-term success.
Role Description Remote Career Opportunity — Your Future Starts NOW! - Make outgoing calls, emails, texts, and chats with clients. - Help families understand and choose the right benefit programs. - Maintain accurate records while delivering excellent service. - Collaborate with teammates to maximize customer satisfaction. - Provide caring support to clients by phone or online. Qualifications - Strong communicators with problem-solving abilities. - Adaptable multitaskers who thrive in fast-paced settings. - Must be willing to get Licensed in Life and Health Insurance. - Reliable and coachable candidates eager to learn and grow. - Must be a U.S. Resident. Requirements - No experience? No problem. We provide complete training. Benefits - High Earnings Potential — Earn $60K–$80K in your first year, with unlimited bonuses. - Fast Career Growth — Promotions, leadership roles, and continuous training await. - Flexible Lifestyle — Full-time or part-time hours designed around your life. - Supportive Team Culture — Work with motivated peers who celebrate wins together. - Free Full Training — No prior experience required; we coach you every step of the way. Company Description Join the fast-growing team at Globe Life AO and take control of your future with flexible schedules, uncapped bonuses, and rapid career growth. Get hired in as little as 24–48 hours and begin building your success story today!
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Python, PyTorch, Azure, JavaScript, NoSQL, SDLC