Senior Machine Learning, Reinforcement Learning Engineer
Sleek
full-time
Posted on:
Location Type: Hybrid
Location: Australia
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Job Level
About the role
- Designing, building, and scaling next-generation ML/RL systems that operate under real-world business constraints.
- Partnering closely with Product, Engineering, and AI teams to translate ambiguous business problems into measurable ML/RL outcomes.
- Owning systems end-to-end — from model optimisation and evaluation through deployment and post-production monitoring.
- Ensuring that ML/RL capabilities are efficient, controllable, observable, and dependable in production.
- Moving beyond generic, large-model approaches, replacing or augmenting them with small, domain-specific models.
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. We are committed to creating and nurturing a diverse and inclusive environment.
- 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. You can also work fully remote from anywhere in the world for 1 month each year
- Financial benefits: We pay competitive market salaries and provide staff with generous paid time off and holiday schedules. Certain staff at Sleek are also eligible for our employee share ownership plan and can share in the upside of our stellar growth trajectory as we work toward listing on a prominent stock exchange in the Asia Pacific region.
- 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. There’s also a range of internal and external facing training programmes we run. We’re also at the forefront of utilising AI in our space and are developing a regional centre of AI excellence. It is our intention that if you leave Sleek, you leave as a more well-rounded person and professional.
- Sleek is also a proudly certified B Corp. Since we started our journey in 2017, we’ve been committed to building Sleek as a force for good. In just over 5 years, we’ve joined a community of industry leaders like Patagonia, Ben & Jerry's, and P&G who are building an inclusive, equitable, and a regenerative economy. We have planted over 29,271 trees to reforest our ecosystem and saved 7 tons of paper from landfills by processing over 1.4M pages through SleekSign. We aim to be Carbon Neutral by 2030.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningreinforcement learningPythonPyTorchmodel optimizationmodel evaluationmodel deploymentdistillationquantizationparameter-efficient fine-tuning
Soft Skills
collaborationproblem-solvingownershipreliability improvementcost management