Through proprietary software and AI, along with a focus on customer delight, Sleek makes the back-office easy for micro SMEs.

Automating the company incorporation, secretarial, filing, Nominee Director, mailroom and immigration processes via custom online robots and SleekSign. Accounting & Bookkeeping: Redefining what it means to do Accounting, Bookkeeping, Tax and Payroll thanks to our proprietary SleekBooks ledger, AI tools and exceptional customer service

FinTech payments: Overcoming a key challenge for Entrepreneurs by offering digital banking services to new businesses

We have around 500 staff with an intact startup mindset.

We have recently raised Series B financing off the back of

Sleek has been recognised by The Financial Times, The Straits Times, Forbes and LinkedIn as one of the fastest growing companies in Asia.

Backed by world-class investors, we are on track to be one of the few cash flow positive, tech-enabled unicorns based out of Singapore.

At Sleek, we are on a mission to streamline operations and elevate customer experience through intelligent automation powered by efficient, reliable, and production-grade ML/RL systems. We are seeking a Machine Learning / Reinforcement Learning Engineer (Applied) who will be a key individual contributor responsible for designing, building, and scaling next-generation ML/RL systems that operate under real-world business constraints.

As one of Sleek's senior applied ML/RL contributors, you will partner closely with Product, Engineering, and AI teams to translate ambiguous business problems into measurable ML/RL outcomes. You will own 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.

You will play a central role in moving beyond generic, large-model approaches, replacing or augmenting them with small, domain-specific models, test-time reinforcement learning, and agentic systems that deliver clear improvements in quality, latency, cost, and reliability. Your work will directly shape how ML/RL is deployed across Sleek's products and internal operations.

Ship High-Impact ML/RL Systems

Deliver production-grade ML/RL systems that create measurable improvements in quality, latency, cost, or reliability

Replace or augment baseline approaches with small,



domain-specific models where they provide superior performance-to-cost trade-offs

Establish Efficient Model Training & Serving (SMOL)

Build and operate efficient training and serving pipelines using distillation, quantization, and parameter-efficient fine-tuning

Maintain benchmark suites covering quality, latency, throughput, memory, and cost

Drive explicit, data-backed trade-offs in model and deployment decisions

Add monitoring, guardrails, and fallback strategies to manage instability and regressions

Design and ship agentic workflows with multi-step planning and execution across tools and data sources

Establish ML/RL Operational Excellence

Implement production monitoring for quality, latency, cost, and failure modes

Ensure training, experimentation, and deployment are reproducible, documented, and observable

Partner closely with Product and Engineering to translate ambiguous problems into shippable ML/RL solutions

Must-have Experience

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

Solid RL fundamentals and experience deploying inference-time optimisation systems (e.g. reward-guided decoding, reranking) under latency and cost constraints

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

For applicants based in Singapore and Australia, this will be a hybrid role. For applicants based in India, Vietnam, and the Philippines, this will be a fully remote role.

Ownership : This shows reliability and helps build trust within the team.



We move rapid and need to know that everyone will see things through to completion and proactively help to get things back on track when challenges arise. It is a key ingredient of self awareness and emotional intelligence.

Regardless of whether you're more analytical or creative in nature, being able to show sound judgement is important to us. It ensures solutions are pragmatic and balance the needs of the organisation, team and customers.

Data driven : We are a data rich business with :15,000 small customers. Each decision we make can impact many more people than we realise - so it's critical that we use sound data to support our strategies and review the success of our initiatives.

Disagreement, conflict and disappointment are a given in a fast moving business where people care about their work. Whether the interviews are held over video call or in person will depend on your location and the role.

A :30 minute chat with the Talent Acquisition Team.

A :45 minute chat with our CTO, where they will dive into some of your recent work situations to understand how you think and work.

We'll make a non-binding offer verbally or over email, followed by a couple of short phone or video calls with references that you provide to us.

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Depending on your role at Sleek, an adverse result on one of these checks may prohibit you from passing probation.

By submitting a job application, you confirm that you have read and agree to our Data Privacy Statement for Candidates, found at sleek.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.

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. 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.

📌 Senior Machine Learning Engineer - AI (India)
🏢 Sleek
📍 India