Abakaai

Abakaai

Machine Learning Engineer

Mountain View, CA

Sponsorship not specified$175k-$275kDetected 77 days ago
PythonAWSGCPAzureKubernetesMachine LearningTensorFlowPyTorchAirflowData EngineeringLLMsA/B TestingResearchCommunicationCollaborationAdaptability

About the role

  • As an early member of the engineering team, you will influence core decisions around model training strategy, experimentation frameworks, distributed infrastructure, and internal best practices.
  • If you thrive in high-ownership environments and want to shape the machine learning foundation of a fast-moving AI company, this role offers an opportunity to make an immediate and lasting impact.

Responsibilities

  • Work closely with data engineering and research teams to develop efficient data workflows, including collection, preprocessing, annotation, versioning, and model integration.
  • Develop tools and automation frameworks that accelerate model experimentation, hyperparameter tuning, and deployment.
  • 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.
  • to be the world's most trusted data partner for AI companies.
  • With our headquarters in Silicon Valley-and teams in Paris, Singapore, and Tokyo-we support global partners with fast, reliable, and scalable data solutions.
  • Whether teams need raw data, curated datasets, or full-cycle data engineering, Abaka AI provides the foundation for building high-performance AI systems.

Requirements

  • 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.
  • Experience with modern infrastructure tools such as Kubernetes, Ray, Airflow, or MLflow, along with cloud-based training environments (AWS, GCP, Azure).
  • 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.
  • Solid understanding of ML system design, including feature pipelines, data loaders, model serving, and evaluation frameworks.
  • 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.
  • Compensation & 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).

Nice to have

  • Master's degree or Ph.D. is preferred.

Compensation

  • Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work at Abaka AI.
  • 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.

Benefits

  • Design, build, and optimize scalable machine learning pipelines for multimodal model training, fine-tuning, and evaluation across text, image, audio, video, and 3D data.
  • Implement and refine training strategies for large-scale AI systems, including vision, video, and diffusion models, ensuring reproducibility, efficiency, and strong model performance.
  • Strong academic background in computer science, artificial intelligence, machine learning, or related fields.
  • This role is eligible for equity, as well as a comprehensive benefits package (health, dental, vision, PTO, flexible work schedule).
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