Staff Machine Learning Engineer

Staff Machine Learning Engineer Needed / $220k-$260k / Santa Clara, CA-Hybrid

This Jobot Job is hosted by: Michael Oktay
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Salary: $220,000 - $260,000 per year

A bit about us:

Based in Santa Clara, CA, we are an AI company that provides a complete AI platform for talent management to help companies find, recruit, and retain workers.

Why join us?

Hybrid (2 Days a Week) Work Environment
Competitive Compensation
Comprehensive Medical, Dental, Vision Insurance
Discretionary Bonus up to 20%
Pre-IPO Equity

Job Details

Responsibilities:

• Own, train, build and deploy cutting edge deep learning models across all products, end to end.
• Build on top of Open Source LLM (Large Language Models) to leverage a diverse dataset.
• Apply innovative solutions from Generative AI
• Create industry best practices for Machine Learning for Recruiting and HR industry around the globe
• Do it responsibly to provide equal opportunity for everyone by extending our internal model fairness platform
• Create innovative algorithms for Machine Learning & AI
• Implement best practices for building AI-enabled products
• Develop AI-based systems for Natural Language Processing (NLP)
• Optimize Machine Learning models for time efficiency, performance, cost, scalability, and accuracy
• Develop tools and processes for automatically train, updating and evaluate LLM (Large Language Models)

Qualifications:

• Strong foundation in Machine Learning (ML), Deep Learning, LLMs and NLP
• Hands-on experience in applying Natural Language Processing solutions to challenging real-world problems.
• Ability to work cross-functionally & interface with data science experts across all of our customer base
• Familiar with LLM (Large Language Models), transformers like BERT, GPTs, T-5, HuggingFace etc.
• Exceptionally strong knowledge of CS fundamental concepts and ML languages ( like Python, C, C , Java, JavaScript, R, and Scala, etc. )
• Ability to innovate, as proven by a track record of software artifacts or academic publications in applied machine learning.
• Prior experience building and deploying machine learning models in production at scale
• Understanding of data and ML systems with the ability to think across stack layers - REST APIs, microservices, data ingestion and processing systems, and distributed systems.
• Extensive experience with scientific libraries in Python (numba, pandas) and machine learning tools and frameworks (scikit-learn, tensorflow, torch, etc.).
• Experience implementing production machine learning systems, working with large-scale datasets, and a solid understanding of machine learning theory.
• Familiar with a cloud-based environment such as AWS, Azure or GCP

Nice-to-Have:

• Metrics-focused and passionate about delivering high-quality models.
• Experience with analyzing large data sets, using Hadoop, Spark
• Familiar with Spark, MLLib, Databricks MLFlow, Apache Airflow and similar related technologies.
• Familiarity with MLOps tools and pipelines (MLflow, Metaflow).
• PhD or Masters in Computer Science or Data Science is preferred.

Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.