Sleek is a company that streamlines operations and elevates customer experience through intelligent automation powered by efficient, reliable, and production-grade ML/RL systems. They are seeking a Machine Learning / Reinforcement Learning Engineer to design, build, and scale next-generation ML/RL systems that operate under real-world business constraints.
Requirements
- Applied ML in Production: ~5+ years building, training, and shipping ML systems using Python and PyTorch, with clear ownership beyond experimentation.
- Efficient Model Training (SMOL): Experience replacing or augmenting large models with smaller, domain-specific ones using distillation, quantization, or parameter-efficient fine-tuning, supported by clear benchmarks.
- Reinforcement Learning & Test-Time Optimization: Solid RL fundamentals and experience deploying inference-time optimisation systems (e.g. reward-guided decoding, reranking) under latency and cost constraints.
- Agentic Systems: Experience building multi-step agents with orchestration concerns such as state, retries, timeouts, and fallbacks, and improving their reliability and cost in production.
- ML/RL Operational Excellence: Experience with reproducible training pipelines, evaluation, monitoring, and production debugging, and collaborating closely with Product and Engineering on constraint-driven problems.
Benefits
- Humility and kindness: Humility is a core attribute we hire for, which means we have a culture of not taking ourselves too seriously and being able to laugh. Kindness is also incredibly important.
- Flexibility: If you need to start early or start late to cater to your family or other needs, we don’t mind, so long as you get your work done and proactively communicate.
- Financial benefits: We pay competitive market salaries and provide staff with generous paid time off and holiday schedules.
- Personal growth: You’ll get a lot of responsibility and autonomy at Sleek - we move at a fast pace so you’ll be making decisions, making mistakes and learning.
