Role Specific Information Job Description About the Role In this role, you will focus on MLOps, supporting cross-functional teams in designing, deploying, and operating machine learning solutions while building scalable infrastructure, tools, and best practices across the Machine Learning Engineering (MLE) ecosystem. What You’ll Do - Collaborate with Data Scientists and Engineers across the full ML lifecycle, including building and scaling ETL pipelines, deploying models into customer-facing applications, and enabling efficient model development through cloud infrastructure and tooling - Design, build, and maintain scalable machine learning infrastructure, including model serving (real-time and batch), training environments, and orchestration systems, with a focus on performance, scalability, and cost efficiency - Contribute to the roadmap for Machine Learning Engineering and Data Science tools, including developing reusable frameworks and standardized solutions to streamline model implementation - Partner with and support Data Scientists by enabling effective use of cloud-based tools and infrastructure, and providing technical expertise across the ML lifecycle - Collaborate with machine learning engineers to share knowledge, improve best practices, and foster a culture of continuous learning and development - Support development and maintain monitoring, alerting, and automated testing frameworks to ensure the reliability, performance, and integrity of data pipelines, models, and infrastructure - Develop, document, and communicate implementations and best practices across the data science lifecycle - Manage and communicate cloud infrastructure costs and budgets to project stakeholders - Stay current with GCP services and evolving best practices in Machine Learning Engineering and MLOps - Additional tasks may be assigned What Skills You Have Required - Experience in MLOps or DevOps practices, including building and operating production ML systems using Docker, Kubernetes, CI/CD pipelines, Git-based version control, API development, model serving (batch and real-time), and automated testing frameworks - Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics or equivalent quantitative field - Experience working with Data Scientists to deploy, scale, and operationalize machine learning models in production environments - 3+ years of experience as a Machine Learning Engineer with a proven track record of successful project delivery - In-depth knowledge of cloud platform, preferably Google Cloud Platform services, particularly Vertex AI, BigQuery and Dataproc. - Extensive expertise with CI/CD and IaC best practices - Extensive knowledge of distributed computing and big data technologies like Spark, Kubeflow, Airflow and SQL - Extensive expertise in Python and machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn) - Experience working in Agile environments with an emphasis on iterative development and continuous delivery Preferred - Master’s Degree - Proficiency in Java or other languages - Retail experience - E-commerce experience - 5+ years of experience in Machine Learning - Experience with optimization techniques and tools (e.g., Gurobi, linear programming, mixed-integer programming) - Experience working with agent based or agentic AI systems, including orchestration of autonomous workflows or LLM-driven agents Essential Functions The requirements listed below are representative of functions you will be required to perform, however you may be required to perform additional functions. Kohl’s may revise this job description at any time. To perform this job successfully, you must be able to perform each essential function satisfactorily. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions, absent undue hardship. - Ability to perform the accountabilities listed in the “What You’ll Do” Section - Ability to comply with dress code requirements - Basic math and reading skills, legible handwriting, and basic computer operation - Ability to maintain prompt and regular attendance and meet scheduling requirements as set by the company - Ability to learn and comply with all company policies, procedures, standards and guidelines - Ability to receive, understand and proactively respond to direction from leadership and other company personnel - Ability to work as part of a team and interact effectively and appropriately with others - Ability to maintain composure and work in a fast paced environment while accomplishing multiple tasks within established timeframes - Ability to satisfactorily complete company training programs - Ability to use a personal computer for tasks such as communicating, preparing reports, etc. - Ability to plan, prioritize and monitor activities across business units - Ability to complete or oversee the completion of assigned projects in a timely manner

Role Description We are seeking a versatile Senior AI/ML Engineer to architect and implement the end-to-end lifecycle of intelligent, data-driven systems. You will bridge the gap between robust data engineering and advanced model development, ensuring that our AI initiatives are grounded in high-quality data and scalable infrastructure. Whether you are fine-tuning Large Language Models (LLMs), building Retrieval-Augmented Generation (RAG) frameworks, or modernizing petabyte-scale data warehouses, you will be the technical lead driving innovation for our clients. As a Senior AI/ML Engineer, you will get to: - Machine Learning, LLMs & GenAI - Model Lifecycle & Development: Lead the design and implementation of ML solutions across the entire lifecycle, including supervised, unsupervised, and deep learning architectures. - LLM Fine-Tuning & Customization: Implement and integrate generative AI models and LLMs, including custom fine-tuning, prompt engineering, and deployment for specialized applications. - RAG & Vector Search: Design and implement Retrieval-Augmented Generation (RAG) architectures using Vertex AI Vector Search to ground model responses in enterprise data. - Multimodal Innovation: Explore and deploy multimodal use cases involving audio, video, or image data. - MLOps & Productionization - Pipeline Orchestration: Implement MLOps practices and tools for model deployment, monitoring, versioning, and pipeline orchestration using Docker, Kubernetes, and Airflow. - Operational Excellence: Operationalize machine learning models on large datasets, ensuring performance tuning, capacity planning, and system monitoring/alerting. - Serving Frameworks: Build and maintain high-quality model serving frameworks and API integrations using FastAPI, Cloud Run, or GKE. - Data Solutions & Infrastructure - Data Warehouse Modernization: Architect complete data warehouse solutions on BigQuery, including star/snowflake schema designs, query optimization, and ETL/ELT pipelines. - Data Pipelines: Build end-to-end data pipelines for structured / unstructured data ingestion, including chunking strategies, embedding generation, and metadata management. - Technical Leadership & Pre-Sales - Technical Leadership & Mentorship: Provide deep technical guidance and mentorship to junior engineers, sharing best practices and troubleshooting techniques while fostering a culture of continuous improvement. - Strategic Pre-Sales: Collaborate as a lead technical expert in strategic pre-sales engagements, delivering expert solution demonstrations and crafting compelling technical proposals. - Workshops: Conduct in-depth workshops to address complex client needs and business strategies. Qualifications - Experience: 5+ years in IT with 4+ years specifically designing and implementing ML solutions, preferably in a technical consulting environment. - Programming Mastery: High proficiency in Python (Pandas, Polars, NumPy, Scikit-learn, XGBoost, TensorFlow/PyTorch) and experience in Java, Scala, or Go. - GCP Expertise: Expert-level experience with Vertex AI (Workbench, Model Garden), BigQuery, and Cloud Storage. - Data Proficiency: Hands-on experience with production-grade data solutions (relational and NoSQL) and preferably big data frameworks like Hadoop or Spark. - Technical Communication: Excellent ability to articulate complex technical concepts to both technical and non-technical audiences. Benefits - Freedom to work from another location—even an international destination—for up to 30 consecutive calendar days per year. - Medical Insurance - Health Benefits - Professional Development: Learning Platform and Certificate Reimbursement - Shift Allowance

In the Accuris we think differently, combining the knowledge and resources of an established company with the unapologetic boldness of a startup. We build software solutions fueled by trusted data that connect to engineering workflows in revolutionary ways, illuminating answers that previously were impossible to find and empowering our clients to envision the future, so they can identify the best course of action in the present. We're disrupting the current digital transformation landscape with state-of-the-art AI developed by a passionate team with a bias to action. Are you ready to join us in building the software that will power the most impactful companies in the world? Our AI team is looking for new talents for the role of Senior ML/AI Engineer critical for success of projects related to Natural Language Processing, Data Capturing, Content Understanding and Information Retrieval domains. You will be responsible for design and engineering aspects of innovative projects related to search, automatic structuring and understanding of unstructured content. Your role is needed to ensure efficient architectures and low-level design of deep learning-based and LLM-based solutions for high-quality deliverables into Accuris products with focus on innovation, scientific research, experimentation, and optimal design. Your duties will include: • Building and optimization of LLM-based solutions.• Building and optimization of ML/DL training, testing and inference pipelines for the latest GPU and CPU hardware and cloud environments.• Design and building of DL/ML-based systems optimized to meet production requirements.• Development and optimization of production inference and data pipelines.• Delivering AI/ML solutions to production.• Analysis, transformation and bootstrapping of datasets. Requirements: • BS degree in math and computer science, or related field.• 4+ years of experience as machine learning engineer or software engineer in ML-related projects.• Experience in Natural Language Processing and/or Information Retrieval.• Solid understanding of deep learning methods.• Experience in ML/DL modeling frameworks like PyTorch and/or other DL frameworks.• Experience with popular modern NLP libraries/frameworks including Hugging Face Transformers.• Algorithmic skills• Developed programming skills (Python)• English language (B1+) The following will hugely increase our interest:• MS or PhD Degree.• Publications in related domain.• Experience with inference and serving engines.• Experience in building LLM-based solutions.• Skills in algorithms and data structures design.• Linux user experience About Company Statement: Accuris delivers essential intelligence that powers decision making. We provide the world's leading organizations with the right data, connected technologies and expertise they need to move ahead. We think differently, combining the knowledge and resources of an established company with the unapologetic boldness of a startup. https://accuristech.com/ Our mission: build an evolvable knowledge and data platform that enables STEM professionals to unlock and deliver innovation to the world's most complex problems. Accuris provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Build, Deploy, and Maintain AI for an Unpredictable World Striveworks helps organizations harness the power of artificial intelligence to solve real-world national security and business challenges by serving as the command center between data, models, and business outcomes. Founded by data scientists and engineers, Striveworks set out to make the journey from deployment to ongoing optimization simple and effective. With Striveworks, organizations aren’t just deploying AI—they’re building systems that remain reliable, adaptable, and ready to scale in an unpredictable world. Mission-critical operations require models that perform where they’re deployed, scale as workloads grow, and adapt rapidly as AI capabilities advance. Striveworks meets these demands—increasing reliability and performance while lowering costs and enabling confident, data-driven decision-making in dynamic environments. The Role As a Senior Machine Learning Engineer at Striveworks, you’ll be challenged—and trusted—on day one to be a core contributor to both the customer-driven projects and the enduring products of the company. You will be a key Striveworks representative and technology builder on projects and solutions that leverage Chariot, our proprietary AIOps platform, and you will inform and contribute to future capabilities of that platform. You will inform, envision, and help extend Striveworks’ core software products. You will work alongside data scientists, software engineers, and DevOps engineers to transform machine learning models into operational capabilities. You’re right for this opportunity if you value and possess technical expertise and enjoy pushing the boundaries of your own capabilities. You’re outcome-driven and are passionate about applying both software engineering and data science to solve real-world problems. You know that building customer-centric solutions, communicating clearly, and capturing repeatable value into productized capabilities are all important. Your day-to-day will include: - Working with customers, engineers, and other stakeholders to define clear requirements that solve customers’ problems and leverage the capabilities of our AI operations platform - Developing machine learning models and custom analytics that are applied to image, video, text, geospatial, time series, and structured data - Orchestrating and automating complex data engineering and analytic pipelines - Envisioning, specifying, and, at times, designing and implementing core product functionality - Opportunities to conduct mission-critical field work This position offers a fully remote work environment, or you can work hybrid/on site at our office in northwest Austin, TX. You will be expected to travel up to 25% of the time. The Right Fit In addition to the specific skills and expertise detailed below, we are looking for individuals who share our values. Sharing a set of values allows us to move at the speed of trust. We value a high-trust work environment where people respect each other and use candor kindly and constructively. We value work that intersects passion and perseverance, we geek out about the potential of our contributions, and we find joy in working hard on things that matter. Finally, we value taking ownership, having agency, and feeling individual responsibility for collective results. Here’s what we’re looking for: - BS degree in computer science, machine learning, or a related discipline and 6+ years relevant experience - Demonstrated experience delivering data-centric systems (e.g., data engineering, data cleaning, ETL pipelines, machine learning, and other production analytics) - Proficiency in programming languages and libraries common to machine learning; excellence in Python is essential, as is knowledge of libraries like TensorFlow, PyTorch, and/or scikit-learn - Proficiency in software engineering fundamentals to include algorithms, data structures, design patterns, and at least one systems programming language (e.g., Go, Rust, C++, Java, Scala, etc.) - Proficiency with modern software engineering tools and processes (Agile, version control, issue tracking, CI/CD, debugging, etc.) - Active Secret (or above) US security clearance - Due to the nature of this role, candidates must have US citizenship The Wish List We’re very interested in candidates who possess the above qualifications, and we appreciate and consider the addition of: - Advanced degree in data science, machine learning, computer science, or a related discipline - Knowledge of relevant architectures and design patterns for client-server systems (e.g., asynchronous programming, REST, GraphQL, React, Vue, Angular) - Experience implementing and deploying software into containerized or cloud environments (e.g., Docker, Kubernetes [k8s], infrastructure as code, major cloud architectures) - Experience with a variety of unstructured data types (e.g., imagery, full motion video, text, acoustic, sonar, RF, telemetry signals) - Experience building agentic systems, agentic workflows, or AI agents - Experience defining, scoping, planning, and delivering complex technical solutions - Experience leading a small team - Experience delivering technology solutions in secure government environments The anticipated base pay range for this position is $160,000–$200,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses. The Benefits - Medical/dental/vision insurance - Voluntary life, long-term disability, accident, and hospital indemnity insurance - HSA and FSA (including dependent care FSA) plans - 401(k) plan - Unlimited PTO - Paid parental leave Check us out on Built In! Striveworks is an Equal Opportunity Employer and does not discriminate in employment on the basis of race, color, religion, belief, sex (including pregnancy and gender identity or expression), national origin, social or ethnic origin, political affiliation, sexual orientation, marital status, disability, genetic information, age, membership in an employee organization, retaliation, parental status, military service, or other non-merit factors. Striveworks will not tolerate discrimination or harassment of any kind. If you require assistance or a reasonable accommodation in the application process, please contact Operations at hr@striveworks.us. In compliance with federal law, all persons hired will be required to verify identity and eligibility to work in the United States and to complete an employment eligibility verification form upon hire. Striveworks is a participating employer in the E-Verify program.