---
title: 'Machine Learning Platform Engineer at Bjak'
canonical: 'https://feeny.ai/job/machine-learning-platform-engineer-bjak-sweden-e2zka0kqh02s'
type: 'job'
last_seen: '2026-09-18'
---

# Machine Learning Platform Engineer at Bjak 

- **Company:** [Bjak ](https://feeny.ai/companies/bjak)
- **Location:** Sweden
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-08-11
- **Last confirmed live:** 2026-09-18
- **Apply:** https://jobs.ashbyhq.com/bjakcareer/7e6faa3e-e2ea-48b8-940d-b45decd9c116

## Job description

## About ActAI

There are over 5 billion users using basic applications today such email, notes, tasks, calendar and they're not AI-native. Our mission is to build proactive applications for anyone in the world, who are not used to complex prompting. We aim to bring intelligence to conversations, errands, organising and workflows, with minimal to no prompting. Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. We believe products will greatly reduce hallucinations. Our objective is to organise anyone's life, allowing us all to spend time on valuable and meaningful things.

## About the Role

As an ML Platform Engineer, you will build the infrastructure and systems that power ActAI's AI capabilities. You will design and operate the systems behind the AI stack, from model training and evaluation to deployment, inference, observability, and continuous improvement. You will work closely with AI engineers, researchers, and product engineers to turn models into reliable, scalable, and cost-efficient production systems. You will build the platforms, tooling, and infrastructure that enable the team to experiment quickly and bring AI capabilities to production with confidence. Focus

- Build and operate the ML infrastructure and platforms powering A1’s AI products
- Design systems for model training, evaluation, deployment, inference, and experimentation
- Build and optimise model serving and inference infrastructure for high-throughput and low-latency workloads
- Improve reliability, scalability, latency, and cost efficiency of AI systems
- Develop reliable pipelines for data preparation, training, evaluation, model release, and continuous improvement
- Build platforms and tooling that enable AI engineers and researchers to experiment, evaluate, and ship models faster
- Develop evaluation and benchmarking infrastructure to measure model quality, performance, and regressions
- Build production observability, monitoring, tracing, and alerting for AI/ML workloads
- Improve AI systems across reliability, scalability, latency, throughput, and cost
- Identify bottlenecks across the ML stack and continuously improve system performance
- Work closely with AI engineers, researchers, and product teams to turn evolving model requirements into production-ready infrastructure

Tech Stack

- Python
- PyTorch / JAX
- LLM and ML serving infrastructure such as vLLM, SGLang, or TensorRT-LLM
- Cloud infrastructure
- Distributed systems
- ML/data pipelines and workflow orchestration
- GPU infrastructure and performance tooling
- Vector databases and retrieval infrastructure

Ideal Experience

- Strong software engineering fundamentals and experience building production systems
- Experience building ML infrastructure, platforms, or production machine learning systems
- Experience with model deployment, inference, evaluation, or data pipelines
- Strong understanding of distributed systems and system reliability
- Ability to write clean, maintainable, production-quality code
- Comfortable working in ambiguous, fast-moving environments
- Bias toward ownership, experimentation, and continuous improvement

Outcomes

- AI infrastructure reliably supports production workloads at scale
- Models can be trained, evaluated, deployed, and improved efficiently
- Inference systems deliver strong latency, throughput, reliability, and cost efficiency
- ML pipelines are reproducible, observable, maintainable, and robust
- Model and infrastructure regressions are detected quickly and diagnosed efficiently
- Common ML infrastructure capabilities become reusable platform primitives rather than being rebuilt for every AI product
- The AI stack can evolve rapidly as new models, architectures, and inference techniques emerge

## About Bjak 

## Company Overview
- **One-liner**: Bjak is Southeast Asia’s leading digital insurance platform, enabling users to compare, purchase, and manage insurance policies and automotive services through a single, AI-powered interface.
- **Entity Type**: Private (Seed Stage)
- **Headquarters**: Selangor, Malaysia
- **Founded**: 2019
- **Founders**: Not publicly available

## Core Business
- **Primary industry**: Insurtech / Financial Services (with a growing automotive service vertical)
- **Target customers**: B2C (individuals seeking insurance and car repairs), B2B (partnerships with 16 insurers and workshop networks)
- **Mission**: “To develop technology‑based solutions to improve financial inclusion.”

## Products & Services
- **Insurance Platform (SaaS / Marketplace)**: Compare quotes from 16 insurers, purchase policies, manage claims, and access 24/7 VIP support. Supported by an AI agent.
- **Car Repair & Service (Marketplace)**: Nationwide online workshop booking for repairs, maintenance, tyre balancing, and more. Includes pay‑later options (installments from RM10/month).
- **Roadside Assistance**: 24/7 towing, flat‑tyre/dead‑battery support, and free replacement car.
- **Extended Warranty**: Coverage for major engine, gearbox, and suspension repairs.
- **Digital Tools**: Insurance Calculator, NCD (No Claim Discount) Checker, Roadtax Calculator.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private); the founder has indicated the company is considering an IPO to expand into Europe.
- **Key Metric**: Annual Revenue estimated at $25 M–$50 M (LinkedIn data for FY2025). Funding raised: Seed round (2019, amount undisclosed, from a single investor).
- **Notable Investors/Partners**: Seed investor not named; partners include 16 Malaysian insurers and a nationwide network of workshops.
- **Growth Signals**: 8 M+ users across Southeast Asia; 32.2% YoY headcount growth (100 employees); 356 open positions (up 278.7% YoY); expanding into 9 countries (Indonesia, UK, Singapore, Thailand, Hong Kong, Taiwan, Japan, Spain, and Malaysia).

## Competitive Advantages
- **Largest insurer network in Malaysia**: Single platform aggregating 16 insurance providers.
- **Integrated ecosystem**: Combines insurance, roadside assistance, and car repair – a one‑stop shop for vehicle ownership.
- **AI & automation**: Uses AI agents to simplify policy selection and claims processes.
- **Speed and user experience**: Quote in under 2 minutes, instant claims handling, and 24/7 support.

## Strategic Focus
- **Geographic expansion**: Entering European markets, with an IPO under consideration.
- **AI‑first product development**: Building new applications that tightly integrate AI to enhance user experience and operational efficiency.
- **Diversification**: Deepening automotive services (repair, warranty, roadside) to increase customer lifetime value.
- **Talent scaling**: Aggressively hiring across engineering, product, marketing, and operations to support growth.

## Why Work Here
- **Culture**: “Results first” – outcomes over effort; direct feedback; flat organization with minimal bureaucracy; high ownership and speed.
- **Work Environment**: Remote‑friendly with a “distributed team of experts” and offices in Malaysia, Thailand, Japan, Taiwan, and the UK. Recruiting globally.
- **Engineering Focus**: Lean, autonomous teams that prioritise product excellence and swift delivery.
- **Career Growth**: Rapidly scaling company with 356 open roles (including Lead, Founder’s Office, iOS Engineer, DevOps, ML Engineer) – opportunities for impact and advancement.
- **Note on Employer Rating**: Current Glassdoor-style rating is 2.3/5 (198 reviews) – potential concerns around work‑life balance and compensation. Candidates should verify recent employee sentiment during interviews.

## Sources
1. [bjak.my](https://bjak.my/en) – Official website (product overview, mission)
2. [bjak.my/en/career](https://bjak.my/en/career) – Career page (culture, values)
3. [jobs.ashbyhq.com/bjakcareer](https://jobs.ashbyhq.com/bjakcareer) – Active job listings and team descriptions
4. [linkedin.com/company/bjak](https://my.linkedin.com/company/bjak) – LinkedIn company profile (employees, revenue, headcount growth, news)

## Other roles at Bjak 

- [Lead, HR Operations](https://feeny.ai/job/lead-hr-operations-bjak-malaysia-q27bpbqdvw6d) — Malaysia
- [Talent Management Manager, OKRs & Performance](https://feeny.ai/job/talent-management-manager-okrs-performance-bjak-united-states-mc5e8f3781ps) — United States
- [Product Lead - AI Neobank App](https://feeny.ai/job/product-lead-ai-neobank-app-bjak-germany-y4y0ddrkx65c) — Germany
- [Product Owner, Technical - AI Neobank](https://feeny.ai/job/product-owner-technical-ai-neobank-bjak-taipei-bk1pvtqhdh3c) — Taipei, Taiwan
- [Product Owner, Technical - AI Investing](https://feeny.ai/job/product-owner-technical-ai-investing-bjak-taipei-p5yb0e604c25) — Taipei, Taiwan
- [Lead Engineer - Wealth Management App](https://feeny.ai/job/lead-engineer-wealth-management-app-bjak-malaysia-0st4aqt3abwc) — Malaysia
- [Head of Strategy and Product](https://feeny.ai/job/head-of-strategy-and-product-bjak-malaysia-pfy0wqkhrazg) — Malaysia
- [CEO Office - AI Neobank App](https://feeny.ai/job/ceo-office-ai-neobank-app-bjak-thailand-3r83tyzfk5sm) — Thailand
- [Business Operations Associate](https://feeny.ai/job/business-operations-associate-bjak-united-kingdom-rk55jka1zbrg) — United Kingdom
- [CEO Office - AI Neobank App](https://feeny.ai/job/ceo-office-ai-neobank-app-bjak-united-kingdom-qrq93mj4r9k3) — United Kingdom