Senior Machine Learning / Reinforcement Learning Engineer

Sleek; India; Remote; INR 1,200,000 - 1,500,000; Full time

Benefits offered by this job

Flexible work hours

Remote work options

Competitive salary

Employee share ownership plan

Generous paid time off

Job summary

A leading company in India is seeking a Machine Learning / Reinforcement Learning Engineer to design and build innovative ML systems. You will work closely with diverse teams, ensuring deployment meets real-world business constraints while improving quality and performance metrics. This role is vital for shaping ML adoption across Sleek's operations, making significant impacts on how technology drives business success. If you thrive in a fast-paced environment and have a strong ML background, we want you on our team.

Qualifications

• 5+ years of experience building ML systems using Python and PyTorch.
• Experience with test-time optimization and agentic systems.
• Solid understanding of reinforcement learning principles.

Responsibilities

• Design and build ML/RL systems for operational deployment.
• Optimize and evaluate models for performance and reliability.
• Collaborate with Product and Engineering teams to translate business problems into ML outcomes.

Skills

Python

PyTorch

Reinforcement Learning

Test-Time Optimization

Model Training

Education

Bachelor's degree in Computer Science or related field

Job description

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

We give Entrepreneurs time back to focus on what they love doing - growing their business and being with customers. With a surging number of Entrepreneurs globally, we are innovating in a highly lucrative space.

We operate 3 business segments:

• Corporate Secretary: Automating the company incorporation, secretarial, filing, Nominee Director, mailroom and immigration processes via custom online robots and SleekSign. We are the market leaders in Singapore with 5% market share of all new business incorporations.
• 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.

Sleek launched in 2017 and now has around 15,000 customers across our offices in Singapore, Hong Kong, Australia and the UK. We have around 500 staff with an intact startup mindset.

We have recently raised Series B financing off the back of >70% compound annual growth in Revenue over the last 5 years. 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.

Requirements

Mission: 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.

Key outcomes in the first 6‑12 months

• 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
• Define and track clear success metrics and benchmarks for all deployed systems
• 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
• Deploy Test‑Time RL & Optimization
• Implement test‑time optimisation (TTRL / TPO) to improve generative or agentic outputs within strict latency and cost budgets
• Introduce reward‑guided decoding or reranking with measurable gains
• Add monitoring, guardrails, and fallback strategies to manage instability and regressions
• Build Reliable Agentic Systems
• Design and ship agentic workflows with multi‑step planning and execution across tools and data sources
• Implement orchestration for long‑running workflows (state, retries, timeouts, idempotency)
• Establish evaluation harnesses and regression tests to track agent reliability and cost over time
• 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
• 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

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.

Behavioural fit is also important at Sleek

Ownership

This shows reliability and helps build trust within the team. We move fast and need to know that everyone will see things through to completion and proactively help to get things back on track when challenges arise. Accountability is really important to us.

Humility

There is so much we don't know. Humility allows for open‑mindedness to feedback and a willingness to learn from others. It paves the way for collaboration and creates a positive work environment. It is a key ingredient of self awareness and emotional intelligence.

Structured Thinking

Our business is complex with many layers (many services, many countries, many cultures). 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.

Can have tough conversations in a positive way

It's not a matter of if, but when difficult interpersonal situations arise. Disagreement, conflict and disappointment are a given in a fast moving business where people care about their work. People that proactively have tough conversations with kindness build empathy, trust and great working relationships.

The interview process

• TA Screening: 30 minute chat with the Talent Acquisition Team
• Take Home Task: Shortlisted candidates will be asked to complete a take home task
• Technical Round: 45 minute interview with the hiring manager
• Behavioural / Soft Skills Fit Assessment: 45 minute chat with our CTO, where they will dive into some of your recent work situations to understand how you think and work
• Offer + reference interviews: 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

Requirement for background screening

Please be aware that Sleek is a regulated entity and as such is required to perform different levels of background checks on staff depending on their role.

This may include using external vendors to verify the below:

• Your education
• Any criminal history
• Any political exposure
• Any bankruptcy or adverse credit history

We will ask for your consent before conducting these checks. 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.com.

Benefits

Some other great things about working at Sleek...

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.