3 months ago

Staff Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Lead end-to-end production ML systems for a proactive AI chat app, translating research into scalable, observable, and reliable ML pipelines and inference engines while collaborating with engineering to integrate ML into backend and frontend products.

Location: London

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
•Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
•Architect and operate scalable inference systems, balancing latency, cost, and reliability.
•Design and maintain data systems for high-quality synthetic and real-world training data.
•Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.

Key Requirements

•Experience shipping real ML systems used by people, with production-grade code and strong reliability characteristics.
•Strong proficiency with Python and ML frameworks such as PyTorch or JAX; experience with GPU-based training/inference.
•Ability to design, implement, and maintain data pipelines, training workflows, evaluation systems, and deployment/inference architectures.
•Experience tuning/ adapting models with methods like LoRA, QLoRA, SFT, DPO, and model distillation.
•Ability to collaborate with application engineering to integrate ML systems into backend, mobile, and desktop products.

Experience:AIMachine learningSoftware

Skills:PythonPyTorchJAXGPUInferenceData pipelinesModel fine-tuningObservabilityDeploymentArchitecture

Languages:English

Tech Stack:PythonPyTorchJAXGPUData pipelinesInference systemsModel trainingLoRAQLoRASFTDPODistillation

Company Brief

BJAK

Bjak is a Malaysia-based insurtech that operates an online insurance comparison and distribution platform across SEA, simplifying purchase and servicing of motor and life insurance using digital tools and AI-enabled services.

Industry: InsurTech

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Headquarters: Selangor, Malaysia

Founded: 2019

Glassdoor: 2.5

Website LinkedIn Glassdoor

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BJAK

3 months ago

Staff Machine Learning Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 22 hours agoStatus: Live

Job Summary

Location: London

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
•Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
•Architect and operate scalable inference systems, balancing latency, cost, and reliability.
•Design and maintain data systems for high-quality synthetic and real-world training data.
•Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.

Key Requirements

•Experience shipping real ML systems used by people, with production-grade code and strong reliability characteristics.
•Strong proficiency with Python and ML frameworks such as PyTorch or JAX; experience with GPU-based training/inference.
•Ability to design, implement, and maintain data pipelines, training workflows, evaluation systems, and deployment/inference architectures.
•Experience tuning/ adapting models with methods like LoRA, QLoRA, SFT, DPO, and model distillation.
•Ability to collaborate with application engineering to integrate ML systems into backend, mobile, and desktop products.

Experience:AIMachine learningSoftware

Skills:PythonPyTorchJAXGPUInferenceData pipelinesModel fine-tuningObservabilityDeploymentArchitecture

Languages:English

Tech Stack:PythonPyTorchJAXGPUData pipelinesInference systemsModel trainingLoRAQLoRASFTDPODistillation

Company Brief

BJAK

Industry: InsurTech

Company Size: Medium (51 to 250 employees)

Growth: Growth Stage Startup

Headquarters: Selangor, Malaysia

Founded: 2019

Glassdoor: 2.5

Website LinkedIn Glassdoor