1 день назад
Lead Machine Learning / Data Science Engineer
90 000 - 200 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Lead Machine Learning / Data Science Engineer (Machine Learning/Data Science): Designing and deploying scalable machine learning systems and data-driven solutions for enterprise clients with an accent on large-scale data processing, cloud platforms, and production ML optimization. Focus on building LLM and agentic AI architectures, implementing RAG and multi-agent orchestration, and providing technical leadership across client engagements.
Location: Reston, VA, USA. Employees must be available to work onsite at a client location or office as requested; remote work is permitted when compatible with and client needs.
Base pay range: $90,000–$200,000 per year.
Company
is a technology consulting firm delivering data-driven and enterprise technology solutions for Fortune 100 companies, mid-sized enterprises, and government agencies.
What you will do
- Design, implement, and deploy end-to-end machine learning and data science solutions for enterprise clients.
- Collaborate with clients, data scientists, engineers, and cross-functional teams to translate business needs into data-driven models and analytical measures.
- Analyze and transform multi-billion-record datasets across AWS, Azure, GCP, and other enterprise data platforms.
- Build production-scale solutions such as recommender systems, natural language processing applications, risk scoring models, and other advanced analytics.
- Optimize and scale machine learning systems for production environments using cloud, containerization, microservices, and automation practices.
- Provide technical leadership and mentoring while supporting client presentations, proposals, business development, and the growth of machine learning and data science practices.
Requirements
- 7+ years of experience delivering data engineering and machine learning solutions on cloud platforms.
- Bachelor’s degree or equivalent combination of education and experience.
- Technical leadership and mentoring experience in data engineering.
- Hands-on experience with Python or Scala, SQL, Spark, NoSQL, cloud data processing frameworks, and large-scale datasets.
- Production experience with Docker, microservices, data warehousing platforms such as Snowflake and Databricks, and model management or versioning.
- Experience delivering production machine learning systems, LLM solutions, prompt engineering, MCP, RAG, agentic AI architectures, conversational UX, prompt evaluation, and multi-agent orchestration.
Culture & Benefits
- Flexible work environment supporting onsite and remote work according to client and business needs.
- Comprehensive benefits including paid time off, health coverage, disability insurance, and paid family leave.
- Certification and tuition support, digital learning courses, mentorship, and career development paths.
- Mental health and well-being support, fertility and family-forming coverage, and a personalized lifestyle benefits stipend.
- Employee resource groups, philanthropic partnerships, and 401(k) matching with no vesting period.
- cannot transfer or sponsor work visas; applicants must already be authorized to work directly for any U.S. employer without visa sponsorship.
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