Senior Machine Learning Engineer

at  Tali AI

Physicians, the backbone of our healthcare system, have long been burdened by excessive administrative tasks and documentation requirements compounded by EMR regulations resulting in the widespread issue of physician burnout. The toll of spending 10-15 hours per week on these tasks has led to a concerning trend known as the “great resignation of healthcare,” with doctors leaving their positions due to overwhelming stress and exhaustion.
Tali AI is dedicated to tackling the issue of physician burnout through the development of a voice-enabled virtual assistant designed specifically for physicians. Our voice enabled AI innovative assistant streamlines their professional lives by significantly minimizing the time spent on documentation and administrative tasks.
Tali AI is looking for a Senior Machine Learning Engineer to play a crucial role in advancing our capabilities in understanding, processing and generating natural language, as well as improving the accuracy and efficiency of our speech recognition systems.

Who You Are:

• You have a degree in Computer Science, Engineering, or a related field with a focus on machine learning, NLP, ASR, or equivalent practical experience.
• You have at least 8 years of professional experience in machine learning engineering, with a strong emphasis on NLP and ASR.
• Proficiency in programming languages such as Python, Java, or C++ for implementing machine learning algorithms and building scalable systems.
• Deep understanding of NLP techniques including text classification, named entity recognition, sentiment analysis, and machine translation.
• Solid grasp of ASR concepts such as acoustic modeling, language modeling, and speech signal processing.
• Strong problem-solving skills and the ability to think creatively to overcome challenges in machine learning projects.
• Excellent communication skills and the ability to collaborate effectively in a team environment.

What You’ll Do:

• Lead the design, development, and implementation of state-of-the-art machine learning models and algorithms for NLP and ASR applications.
• Conduct research and stay up-to-date with the latest advancements in NLP and ASR to continuously enhance our technology stack.
• Collaborate with cross-functional teams including software engineers, data scientists, and product managers to integrate machine learning solutions into our products and services.
• Analyze and preprocess large volumes of text and speech data to extract meaningful insights and features for model training.
• Optimize model performance and scalability to meet stringent latency and throughput requirements.
• Conduct thorough experimentation and evaluation to assess the performance of NLP and ASR models and identify areas for improvement.
• Provide mentorship and guidance to junior members of the machine learning team, fostering a culture of continuous learning and innovation.

Our Core Values

• Growth: we have a growth mindset; we want to learn and improve a little (or a lot!) every day.
• Purpose: we care about our team and our community; we understand the purpose of our work and take it seriously.
• Innovation: we’re all about innovation and cutting edge technology; we don’t shy away from a challenge.

Perks and Benefits

• Comprehensive health and wellness benefits package from day one
• Three weeks paid vacation and additional company-wide holiday between Dec 25 - Jan 1
• Half day Fridays (35-hour work week)
• “Knowledge Dollars” to invest in annual professional development
• Quarterly socials & company outings
• Fully remote work

• Lead the design, development, and implementation of state-of-the-art machine learning models and algorithms for NLP and ASR applications.
• Conduct research and stay up-to-date with the latest advancements in NLP and ASR to continuously enhance our technology stack.
• Collaborate with cross-functional teams including software engineers, data scientists, and product managers to integrate machine learning solutions into our products and services.
• Analyze and preprocess large volumes of text and speech data to extract meaningful insights and features for model training.
• Optimize model performance and scalability to meet stringent latency and throughput requirements.
• Conduct thorough experimentation and evaluation to assess the performance of NLP and ASR models and identify areas for improvement.
• Provide mentorship and guidance to junior members of the machine learning team, fostering a culture of continuous learning and innovation