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Commission Machine Learning Startup Jobs in Virginia

Morgan Stanley's Machine Learning Research Department is responsible for working across the Firms ... commission earnings, incentive compensation, discretionary bonuses, other short and long-term ...

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Commission Machine Learning Startup information

What is the difference between Commission Machine Learning Startup vs Data Scientist?

AspectCommission Machine Learning StartupData Scientist
CredentialsDegree in Computer Science, Data Science, or related fields; experience with ML modelsDegree in Computer Science, Statistics, or related fields; proficiency in programming and data analysis
Work EnvironmentStartup setting, fast-paced, innovative projects, often remote or flexibleCorporate or research environment, collaborative teams, often office-based
Industry UsageTech startups, AI-focused companies, innovative product developmentTech firms, finance, healthcare, research institutions
Search & Comparison IntentUnderstanding roles in ML startups, freelance or commission-based opportunitiesCareer development, skill requirements, industry roles

Commission Machine Learning Startup roles focus on developing ML solutions within startup environments, often with flexible or freelance arrangements. Data Scientists typically work in established companies, applying statistical and programming skills to analyze data. Both roles require similar credentials but differ in work setting and industry focus.

What are the most commonly searched types of Machine Learning Startup jobs in Virginia? The most popular types of Machine Learning Startup jobs in Virginia are:
What cities in Virginia are hiring for Commission Machine Learning Startup jobs? Cities in Virginia with the most Commission Machine Learning Startup job openings:

Machine Learning Engineer with Security Clearance

Synthbee, Inc.

Crystal City, VA โ€ข On-site

Other

Posted 24 days ago


Job description

SynthBee is seeking a Machine Learning Engineer who can take AI models from research to productionโ€”integrating agentic AI systems into our product. This role is engineering-focused, working alongside a research counterpart to build and deploy real-world AI automation tools. This is an ideal role for a generalist who has built AI applications before and has strong intuition for AIโ€”especially in deploying AI powered applications and AI agents. At SynthBee weโ€™re building Collaborative Intelligenceโ„ข maximizing the potential of people and computers working together. CIโ„ข will help humans solve the most important scientific, engineering, design, and creative challenges of our time. And create joy in the process. What Youโ€™ll Do Develop AI-driven reasoning agents and frameworks for automating complex tasks. Build and optimize RAG (Retrieval-Augmented Generation) pipelines Distill and fine-tune AI models to improve reasoning, automation, and decision-making. Deploy AI models into scalable, production-ready systems using Python and cloud-based infrastructure. Collaborate closely with researchers to operationalize AI advancements into real applications. What Weโ€™re Looking For Proven experience building and deploying AI applications (ideally in a startup or fast-moving environment). Hands-on expertise with agentic frameworks (e.g., AutoGen, CrewAI, LangChain, DSPy, or Haystack). Strong background in AI-powered automation & orchestration workflows. Experience working with vector databases and retrieval systems (e.g., LlamaIndex, FAISS, Pinecone, Weaviate). Some experience with fine-tuning AI models is a big plus, but not required. Solid coding skills in Python, familiarity with cloud deployment tools (AWS, GCP, or Azure). Who Should Apply? Youโ€™ve built AI-powered applicationsโ€”at a startup, in open-source projects, or in a side hustle. Youโ€™re excited about agentic AI and building autonomous workflows that solve real problems. You want to be part of a small, fast-moving team where your work directly impacts the product. Youโ€™re comfortable with ambiguity and love figuring things out in a fast-paced startup.