ASTRABRIGHT ANALYTICS & KNOWLEDGE ALLIANCE, INC - Machine Learning Engineer

and teams in Paris, Singapore$175k - $275k+ Equity2w ago

In Office Mid APAC Cloud Computing Artificial Intelligence Machine Learning Engineer JAX Python Kubernetes MLflow Airflow

Requirements

• Strong academic background in computer science, artificial intelligence, machine learning, or related fields. Master’s degree or Ph.D. is preferred. • 3+ years of experience in applied machine learning or ML engineering, with a demonstrated ability to deliver production-ready models or pipelines. • Proficient in Python and ML frameworks such as PyTorch, TensorFlow, or JAX, with hands-on experience in large-scale distributed training and inference systems. • Familiarity with multimodal data processing (e.g., text-image pairing, video understanding, speech-audio modeling) and dataset optimization for model training. • Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks. • Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure). • Excellent communication and collaboration skills, capable of working effectively across engineering, research, and product teams to accomplish shared goals. • Self-driven and adaptable, comfortable operating in a fast-paced startup environment, and able to demonstrate strong ownership and urgency in execution.

Responsibilities

• Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data. • Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration. • Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance. • Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment. • Identify and address performance bottlenecks in data or training pipelines to improve throughput, stability, and resource utilization. • Collaborate with product and infrastructure teams to ensure smooth integration of model outputs into both internal and client-facing applications. • Support internal best practices for model governance, experiment tracking, and documentation to maintain high engineering standards and reproducibility.

Benefits

• The base salary range for this position is $175,000 - $275,000 USD annually. • Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI. This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).