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About the Company
We are a fast-growing, product-focused AI company operating at the intersection of applied research and real-world deployment. Our team partners closely with customers to design, build, and productionize advanced machine learning systems that solve complex, high-impact problems.
We emphasize ownership, speed, and innovation-empowering engineers to take ideas from concept to production while staying at the forefront of emerging AI technologies.
About the Role
We are seeking a Senior Machine Learning Engineer who thrives at the intersection of applied research and hands-on engineering. This role blends approximately 30% research (reading, synthesizing, and contributing to academic work) with 70% production-focused development.
You will play a key role in evaluating cutting-edge techniques and translating them into scalable, real-world systems. This is a highly autonomous role where you will own end-to-end ML initiatives, especially for new problem domains, building solutions from 0 1.
What You'll Do
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Applied Research (30%)
- Stay at the forefront of machine learning by reading and synthesizing academic papers in areas such as:
- Deep Learning
- Large Language Models (LLMs)
- Reinforcement Learning
- Multimodal AI
- Publish research findings internally and externally to guide engineering direction
- Evaluate emerging techniques and determine their applicability to real-world use cases
- Contribute to technical thought leadership and influence company-wide ML strategy
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Engineering & Development (70%)
- Design, build, and deploy production-grade machine learning systems
- Develop scalable pipelines for training, evaluation, and inference
- Work with modern ML frameworks and tooling to train and optimize models
- Implement and iterate on models across domains including language, vision, and multimodal data
- Collaborate cross-functionally to integrate ML systems into customer-facing products
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Ownership & Execution
- Lead 0 1 builds for new customer domains or problem spaces
- Own the full lifecycle: problem definition, modeling, experimentation, deployment, and iteration
- Operate with a high degree of autonomy while maintaining strong alignment with team goals
- Mentor junior engineers and contribute to best practices across the team
What We're Looking For
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Core Requirements
- 4+ years of experience in Machine Learning Engineering or Applied Research roles
- Strong programming skills in Python and experience with ML ecosystems
- Hands-on experience with:
- Deep Learning frameworks (e.g., PyTorch, TensorFlow)
- Large Language Models (LLMs) and/or generative AI systems
- Model training, evaluation, and optimization techniques
- Experience reading and applying academic research in practical settings
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Research Background (Preferred)
- Prior experience publishing or contributing to research papers (industry or academia)
- MS or PhD in Computer Science, Machine Learning, or a related field is a plus
- Ability to bridge theoretical concepts with production systems
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Nice-to-Have Experience
- Reinforcement Learning (RL) or RLHF
- Multimodal systems (vision, video, audio, etc.)
- AI safety, security, or reliability in production environments
- Experience working in ambiguous, fast-paced environments or startup settings
What Makes This Role Unique
- High ownership: You will lead initiatives end-to-end, not just contribute to isolated components
- Research + production blend: Directly apply cutting-edge research to real-world systems
- 0 1 opportunities: Build entirely new solutions for emerging customer needs
- Impact-driven work: Your contributions will shape both product direction and technical strategy
Oscar Associates Limited (US) is acting as an Employment Agency in relation to this vacancy.
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