Fully Remote Position Preferred Locations: Midwest based: Indianapolis, IN or IL, Chicagoland Area preferred Who We Are: K1x is the leading data distribution platform for alternative investments. Simply put, our mission is to digitize the K-1 ecosystem. Our AI-powered K-1 extraction technologies surpass all other competition and we’re the first to produce a digital K-1. Learn more at www.k1x.io About the role: We are seeking a highly skilled and experienced Machine Learning Engineer to join our dynamic team. The ideal candidate will have a strong background in natural language processing (NLP) and extensive experience working with unstructured and semi-structured data such as financial statements and tax documents. As a Machine Learning Engineer, you will play a critical role in developing and implementing machine learning models that enhance our software’s ability to accurately and efficiently process partnership accounting and tax documents. If you are an experienced Machine Learning Engineer or Data Scientist looking for an exciting opportunity to work on challenging problems and deliver machine learning products, we would love to hear from you. Join our team and help shape the future of alternative investments management and distribution! Responsibilities - Develop and optimize machine learning models for parsing, extracting, and categorizing data in PDF tax documents. - Collaborate with cross-functional teams to integrate machine learning solutions into our software products. - Apply statistical analysis to identify signals, trends, and insights that can inform product development. - Mentor and guide junior data scientists and team members, fostering a collaborative and innovative work environment. Requirements: - Masters’ or PhD in Computer Science, Mathematics, Statistics, Data Science, or a related field - 6+ years of relevant industry experience as a data scientist, with a focus on NLP/NLU projects - Demonstrated experience leading end-to-end data science project implementations - Excellent problem-solving skills with the ability to synthesize and communicate complex technical results to senior leaders and nontechnical audiences - Proficiency in Python and a strong understanding of machine learning frameworks and libraries (e.g. scikit-learn, PyTorch, spaCy, Huggingface)

• Lead the development of tools and processes using LLMs, Diffusion Models, and AI Agents • Oversee the deployment of AI-driven models for enhancing content creation • Evaluate the impact of solutions for engineering and AI excellence • Collaborate with cross-functional teams for aligning technical initiatives • Hire and inspire a high-performing team of AI professionals • Foster a culture of continuous learning and innovation • Provide strategic guidance and facilitate informed decision-making • Communicate team progress and achievements to senior leadership

• Own and evolve our multi-engine inference platform, supporting a variety of model types and serving requirements. • Build and improve production ML pipelines — taking models from experimentation to reliable, high-throughput serving. • Define and implement model versioning, rollout, rollback, and lifecycle management strategies that ensure reproducibility and operational reliability. • Define and enforce serving-layer SLAs, including latency, availability, GPU utilization, Time-to-First-Token (TTFT), and Inter-Token Latency (ITL). • Build observability, monitoring, alerting, and operational tooling for production inference systems. • Apply software engineering best practices, including testing, CI/CD integration, and reproducibility across ML workflows. • Optimize inference performance through efficient resource utilization, hardware-aware serving strategies, and cost-conscious infrastructure design. • Ensure ML serving systems are secure, scalable, and operationally resilient. • Partner with ML, Data, Product, and DevOps teams to turn ideas into production systems, driving the technical decisions on serving and scale.

• Design, build, and operate Samsara’s end-to-end ML platform spanning training, experimentation, batch and online inference, and edge deployment • Partner with product and applied ML teams to design, launch, and iterate ML-powered features (e.g., backend CV models, EcoDriving insights, LLM-based reporting) • Lead throughput and cost estimation for new ML features—from early-stage exploration to production-scale capacity planning • Collaborate on experiment design and evaluation, including defining success metrics, structuring A/B tests or offline evaluations • Evolve shared training and experimentation infrastructure (e.g., job orchestration, cluster configuration, environment management) • Design and operate scalable online and batch inference systems (Ray- and Spark-based) • Partner with firmware and edge teams to define workflows for packaging, validating, and deploying models to Samsara devices • Own the reliability, observability, and security posture of ML systems across cloud and edge environments • Provide Staff+/Senior-Staff-level technical leadership by setting architecture and strategy for ML infrastructure • Drive strong developer experience through documentation, office hours, and best practices • Own or co-own end-to-end technical delivery for high-priority or high-risk initiatives.