ML Solution Architect (Early Talent)

**This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a ML Solution Architect (Early Talent) based in United States.** This opportunity is designed for early-career AI engineers who want hands-on experience building and optimizing machine learning solutions. You will work alongside experienced architects and engineering teams to develop LLM-powered applications and explore the future of AI infrastructure. The role combines technical experimentation, customer-focused solution design, and practical learning in a fast-moving AI environment. You will contribute to projects involving generative AI, inference optimization, benchmarking, and scalable deployment workflows. This paid temporary program provides mentorship, real-world technical challenges, and exposure to cutting-edge AI technologies. High-performing candidates may have the opportunity to transition into a full-time Solutions Architect position. ### Accountabilities: As an ML Solution Architect (Early Talent), you will support the development, testing, and optimization of AI solutions while learning how scalable machine learning applications are designed and deployed. You will collaborate with senior technical experts and contribute to projects that improve AI application performance and usability. - Build and test LLM-based solutions and applications using inference services, including multimodal models across text, vision, and audio. - Assist senior Solutions Architects with prompt engineering, model selection, benchmarking, and inference optimization. - Conduct performance and quality experiments to support proof-of-concept projects and technical evaluations. - Contribute to internal tools, automation workflows, and processes that improve solution delivery. - Collaborate with backend engineering teams to understand platform capabilities and deliver effective AI solutions. - Explore and apply best practices for deploying, tuning, and scaling generative AI applications. - Communicate technical findings clearly and support documentation of experiments, results, and recommendations. ## Requirements: The ideal candidate is an aspiring AI engineer or technical professional with strong programming fundamentals and a passion for machine learning, generative AI, and cloud-based technologies. You should be curious, collaborative, and excited to learn through hands-on technical projects. - Currently pursuing or recently completed a BSc, MSc, or PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field. - Strong Python programming skills and experience developing software solutions. - Hands-on experience with generative AI technologies and machine learning frameworks such as PyTorch and Transformers. - Understanding of machine learning concepts, model architectures, and AI application development. - Strong communication skills with the ability to explain technical concepts to different audiences. - Experience or familiarity with LLM deployment tools such as vLLM, SGLang, or TensorRT-LLM is a plus. - Knowledge of inference optimization techniques, including quantization, batching, caching, and routing, is preferred. - Experience with APIs, cloud platforms, MLOps tools, Docker, Kubernetes, Git, or open-source AI projects is a plus. - Ability to work independently, collaborate effectively, and adapt in a rapidly evolving technical environment. ## Benefits: - Paid 3-month remote contract opportunity. - Competitive compensation range of **$102–$126 USD**. - Potential pathway to a full-time Solutions Architect opportunity for strong performers. - 100% company-paid medical, dental, and vision coverage for employees and families. - 401(k) plan with up to 4% company matching and immediate vesting. - Paid parental leave, including 20 weeks for primary caregivers and 12 weeks for secondary caregivers. - Remote work reimbursement of up to $85/month for mobile and internet expen…