Adapter
Machine Learning Engineer
United States - Remote
Sponsorship not specified$180k-$225kDetected 8 days ago
PythonDistributed SystemsMachine LearningTensorFlowPyTorchNLPLLMsRecruitingResearchCollaboration
About the role
- As these technologies become increasingly accessible, our aim is to make their capabilities empowering, trustworthy, and useful to real people in the real world.
- We recognize the importance of being early movers in this field, and have assembled a well-supported and passionate team to do so.
Responsibilities
- Work with large datasets, perform data preprocessing, and engineer relevant features to enhance model performance.
- Build frameworks that allow us to iterate and evaluate model versions (ranking, accuracy, latency).
- Monitoring and Maintenance: Implement monitoring solutions to track model performance in real-time and perform regular maintenance and updates as needed.
- Collaboration: Work closely with cross-functional teams, including data scientists, software developers, and business analysts, to understand requirements and deliver impactful solutions.
- Implement monitoring solutions to track model performance in real-time and perform regular maintenance and updates as needed.
- Work closely with cross-functional teams, including data scientists, software developers, and business analysts, to understand requirements and deliver impactful solutions.
Requirements
- Experience with large-scale data processing and distributed systems
- Proficient in designing, developing, and operating fine-tuning pipelines in production environments
- Strong programming skills in Python, and proficiency in machine learning libraries such as PyTorch, Tensorflow etc.
- Work Experience:
- Benefits:
- Early stage equity
- Comprehensive health insurance
- Generous PTO
- Remote and in person cultures that promote collaboration
- Full compensation packages are based on candidate experience and certifications.
- United States - Remote Pay Range
Nice to have
- 3+ years of experience in similar role, focus on developing and deploying ML models in production environments
- Startup experience is a plus
- Experience with optimizing models for size, cost, and latency is a plus.
Skills
- Our story: The widespread adoption of intelligent technologies powered by automation, AI, ML, and knowledge graphs is accelerating.
Compensation
- $180,000 - $225,000 USD
Benefits
- Deploy Models at Scale: Collaborate with software engineers to deploy machine learning models into production, ensuring seamless integration with existing systems.
- Research and Innovation: Stay abreast of the latest advancements in machine learning and contribute to the research and development of innovative solutions.
Company info
- The widespread adoption of intelligent technologies powered by automation, AI, ML, and knowledge graphs is accelerating.
- Adapter was founded in 2022 by Adam Ghetti and Dr.
- David Bader, with the support of some of the most esteemed Tier 1 Silicon Valley firms and individual entrepreneurs.
- We are a small but dedicated team, currently working towards solving a significant problem.
- What we are looking for:
- We are looking for a Machine Learning Engineer who will play a critical role in fine-tuning transformer-based models using automation pipelines and implementing real-time fine-tuning pipelines in production environments.
- You will partner with a brilliant team of designers, engineers, and innovators and will be at the cutting edge of some of the most interesting consumer use-cases for intelligent technologies.
- We have established a culture that promotes both remote work and in-person collaboration, with team members currently dispersed between Austin, NYC, and the Bay Area.
- We believe that the integration of these two elements allows for maximum productivity and creativity as we strive to achieve our goal.
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