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Machine Learning Platform Engineer

Job Overview

Location

Sweden

Job Type

Full-time

Category

Machine Learning Engineer

Date Posted

August 11, 2026

Full Job Description

đź“‹ Description

  • • As an ML Platform Engineer, you will build the infrastructure and systems that power A1'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 on building and operating the ML infrastructure and platforms powering A1’s AI products
  • • Design systems for model training, evaluation, deployment, inference, and experimentation
  • • Build and optimize 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 includes Python, PyTorch / JAX, LLM and ML serving infrastructure, cloud infrastructure, distributed systems, ML/data pipelines and workflow orchestration, GPU infrastructure and performance tooling, and vector databases and retrieval infrastructure
  • • Ideal experience includes strong software engineering fundamentals, 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, and comfort working in ambiguous, fast-moving environments
  • • Outcomes include AI infrastructure reliably supporting production workloads at scale, models being trained, evaluated, deployed, and improved efficiently, inference systems delivering strong latency, throughput, reliability, and cost efficiency, ML pipelines being reproducible, observable, maintainable, and robust, model and infrastructure regressions being detected quickly and diagnosed efficiently, common ML infrastructure capabilities becoming reusable platform primitives, and the AI stack evolving rapidly as new models, architectures, and inference techniques emerge

🎯 Requirements

  • • Strong software engineering fundamentals
  • • 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
  • • Comfort working in ambiguous, fast-moving environments

🏖️ Benefits

  • • Opportunity to work on a proactive smart assistant for everyday users
  • • Chance to build the infrastructure and systems that power A1's AI capabilities
  • • Collaborative work environment with AI engineers, researchers, and product engineers
  • • Opportunity to turn evolving model requirements into production-ready infrastructure
  • • Professional growth and development in the field of machine learning and AI
  • • Competitive salary and benefits package
  • • Flexible work arrangements and remote work options
  • • Access to cutting-edge technology and tools
  • • Opportunities for professional growth and development
  • • Collaborative and dynamic work environment
  • • Recognition and rewards for outstanding performance
  • • Opportunities for career advancement and professional growth

Skills & Technologies

Python
PyTorch
Onsite

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About Bjak Sdn. Bhd.

Bjak operates Malaysia’s largest digital auto-insurance marketplace, enabling instant price comparison and online purchase of motor coverage from leading insurers. The platform uses proprietary technology to simplify complex tariffs, deliver personalised quotes and e-policy issuance within minutes, eliminating paperwork and agent visits. Licensed by Bank Negara Malaysia, Bjak also offers road-tax renewal, accident assistance and claims support, serving millions of drivers nationwide while partnering with insurers to increase digital distribution efficiency and customer reach.

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