Remote Machine Learning Engineer jobs open to Asia.

C1 English, own agent harnesses, multi-agent workflows, fine-tuning open-source models, overlap with EU afternoons

CVEDIACVEDIA builds computer vision models, trained on synthetic data, that run in products on server and edge hardware.

Python · Java · Kotlin

Required: bachelor’s or master’s in CS/ML/data science or related quantitative field and 7+ years production ML experience; NLP/LLM, transformers, prompt engineering, fine-tuning and alignment; Python plus familiarity with Kotlin, Java or Go; evaluation/benchmarking and precision/recall trade-offs; data storytelling and a visualization tool; cloud ML (AWS/GCP), Kubernetes/Docker and Spark/SQL; analytical, communication and agile problem-solving skills. Preferred: trust/safety or AI red-teaming; inference optimization/quantization; AI governance/provenance; streaming or graph systems.

AtlassianAtlassian is a Sydney-based B2B software company specializing in collaboration tools for software development and project management, serving a global market.

Python · SQL

3 years of experience, PhD in Statistics, Mathematics, Data Science, or related field, 3–6 years in data science, ML, or data analytics, Strong statistical foundation, Hands-on experience with LLMs and AI agents, Proficiency in Python and SQL, Critical thinking about data quality and model outputs, Clear communication skills

Python · Docker

4 years of experience, Generative AI, MLOps lifecycle management, Python, Docker, Apache Spark, Client-facing consulting, Production-grade AI/ML pipelines, Multi-agent orchestration, Retrieval Augmented Generation (RAG) Systems, Data pipeline orchestration

Mutt DataMuttdata is a data and AI consultancy that builds data platforms and machine learning systems, such as forecasting and recommendation models, for client companies.

Python · AWS · Azure

8+ years applied ML, Python, transformers/LLMs, AWS/GCP/Azure real-time inference, select Indian states

TwilioTwilio provides a customer engagement platform that combines communications, customer data, and AI.

Python · AWS · Azure

10+ years applied ML, Python, LLM orchestration/embeddings/vector stores, AWS/GCP/Azure, select Indian states

TwilioTwilio provides a customer engagement platform that combines communications, customer data, and AI.

Python · AWS · Azure

5+ years applied ML, Python, LLM orchestration/embeddings/vector stores, AWS/GCP/Azure, select Indian states

TwilioTwilio provides a customer engagement platform that combines communications, customer data, and AI.

Python · SQL · Azure

Databricks orchestration, CI/CD (Azure DevOps), Advanced Python, SQL, Delta / Unity Catalog, MLflow management, Deployment automation

Mutt DataMuttdata is a data and AI consultancy that builds data platforms and machine learning systems, such as forecasting and recommendation models, for client companies.

Python · Java · Kotlin

8+ years software leadership, end-to-end ML systems, MLOps, search ranking, Java/Python/Kotlin

AtlassianAtlassian is a Sydney-based B2B software company specializing in collaboration tools for software development and project management, serving a global market.

Python · AWS

What We're Looking For 5+ years of software/ML engineering experience, including hands-on work building or maintaining evaluation, testing, or measurement infrastructure for ML systems. Direct experience with foundation model evaluation and benchmarking beyond using APIs — experience gained at a foundation model lab or similarly frontier research environment is strongly preferred. Demonstrated ability to own an evaluation solution end-to-end — from initial design and dataset/methodology creation through pipeline build, deployment, and production monitoring — with minimal hand-off. Direct experience designing evals for LLMs and/or AI agents — e.g., benchmark design, LLM-as-judge pipelines, human annotation platforms, or A/B and offline/online eval frameworks. Strong programming skills in Python, PyTorch / Tensorflow and experience building production-grade data/ML pipelines. Hands-on knowledge of key model training and evaluation platforms, particularly AWS (e.g., SageMaker, Bedrock) and Databricks (e.g., MLflow, Unity Catalog, Delta Lake). Solid grounding in applied statistics — comfortable reasoning about sample size, variance, significance testing, and the limitations of aggregate metrics. Working knowledge of how LLMs are trained and adapted (pretraining, SFT, RLHF/RLAIF/DPO) and how eval signal feeds into that lifecycle. Experience with agentic architectures — tool calling, multi-step planning, memory, orchestration frameworks — and the unique evaluation challenges they introduce. Familiarity with eval and observability tooling (e.g., internal or open-source frameworks for tracing, dataset versioning, experiment tracking). Excellent cross-functional collaboration skills; able to translate ambiguous product/research questions into concrete, measurable eval criteria. A bias toward rigor and skepticism — you instinctively question whether a metric is actually measuring what it claims to. Bonus Points We prioritize candidates with direct experience in the following areas: Post-training & evals: hands-on experience with post-training techniques (SFT, RLHF, RLAIF, DPO) and the evaluation methodologies used to validate them, ideally gained at a frontier model labs Model benchmarking: experience building, running, or maintaining benchmark suites used to track and compare frontier model capabilities across training runs and releases. Data quality: experience with the data quality side of model training — curation, filtering, deduplication, and quality scoring of pretraining and post-training datasets.

CheggChegg is a student-focused online learning company whose Busuu brand offers AI-powered language courses with feedback from a community of native speakers.

Python · SQL

5 years of experience, Production ML model deployment, Python, SQL, Real-time data pipelines, Ad tech experience, Big data solutions, Model evaluation and optimization, Cross-functional collaboration, Experimentation frameworks, Kedro, PyTorch, Databricks