Junior Machine Learning Engineer
As a Junior Machine Learning Engineer, you will be a core contributor to both customer-driven projects and the enduring products of the company. Working alongside data scientists, software engineers, and DevOps engineers, you’ll develop AI capabilities, custom analytics, and mission-critical solutions applied to image, video, text, geospatial, time series, structured, and other data. You will orchestrate complex data engineering pipelines in agentic and traditional architectures. Your work will inform the future of Chariot, our proprietary AI operations platform, and your impact will be felt across mission-critical deployments and direct customer contact.
What it’s like here
We lead with trust, treat each other with respect, and use candor consistently, kindly, and constructively. We care deeply about our work, and we find genuine satisfaction in doing it well. Above all, we take ownership—because we feel the weight of collective results personally. We are looking for people who share these values and are eager to put them into practice.
What we’re looking for
A BS degree in computer science, machine learning, or a related discipline and 0–2 years of relevant experience
Strong proficiency in Python including experience with libraries and frameworks like PyTorch, TensorFlow, and/or scikit-learn
Strong software engineering fundamentals and experience with at least one systems programming language
Exposure to the development and use of machine learning models, through either coursework or practical experience
Familiarity with modern software engineering tools and processes
US citizenship and eligibility and willingness to obtain and maintain a US security clearance (Secret or above)
The following isn’t required, but we’d love to see it:
Demonstrated software development through personal, academic, or open source projects
Advanced degree in computer science, data science, machine learning, or a related discipline
Excellence in Python and deep knowledge of machine learning libraries
Experience performing exploratory data analysis on structured and unstructured data
Experience with agentic workflows, LLM evaluation, testing, observability, or guardrails
Familiarity with vector databases, embeddings, retrieval-augmented generation (RAG), or other modern AI application patterns
Knowledge of relevant architectures and design patterns for client-server systems
Experience implementing and deploying software in containerized or cloud environments, using tools such as Docker, Podman, or Kubernetes (K8s)
Experience working with asynchronous programming, concurrency, or event-driven architectures
Active Secret (or above) US security clearance
This position offers a hybrid/on-site work environment at our office in Austin, TX. You will be expected to travel up to 25% of the time.
Compensation
The anticipated base pay range for this position is $100,000–$130,000/year. Striveworks’ total compensation package includes a competitive base salary, equity grants, and cash bonuses.