Senior Machine Learning Engineer
2 months ago
Autonomize, Inc is seeking a highly motivated Senior ML Engineer to join our team on a journey to help healthcare organizations unlock dark data.
Autonomize is on a mission to help organizations make sense of the world's data. We help healthcare organizations harness the full potential of data to impact human health outcomes. Unstructured dark data contains nuggets of information that when paired with human context will unlock some of the most impactful insights for most organizations, and it's our goal to make that process effortless and accessible.
We are an ambitious team committed to human-machine collaboration. Our founders are serial entrepreneurs passionate about data and AI and have started and scaled several companies to successful exits. We are a global, remote company with expertise in building amazing data products, captivating human experiences, disrupting industries, being ridiculously funny, and of course scaling AI.
We are a humble yet hungry group, always learning, always experimenting and always giving our best in everything we do. The company is still very young, and you will be joining the core engineering team, and it provides you the opportunity to take on more responsibility, break glass and change the world.
About the Role :
This is a hands-on role, where you will build the team and function to Autonomize platform (Data, code, pipelines). We are looking for the "learn-it-all" type and not the "know-it-all". In this role, you will be responsible for the design and implementation of AI/ML solutions, including the integration of backend ML pipelines into full stack applications in collaboration with other ML/NLP/Fullstack team members.
Here is what we are looking for in our teammate (Must-have technical & industry competencies):
1. Hands-on coding experience - Strong python skills.
2. Experience in Deep Learning deployments in production environments.
3. Ability to contribute to multiple client initiatives , feature implementations & delivery.
4. 4+ years experience in building NLP systems (preferably for healthcare / life sciences use cases).
5. Strong understanding and experience working with Transformer Models like BERT, CLIP, GPT, T5, etc.
6. Deep familiarity in building and deploying language models, LLMs,QA., Search systems.
7. Deep familiarity of various deep learning training techniques - few/zero shot learning, transfer learning, federated learning.
8. Experience using frameworks like Django, Flask etc to package NLP systems as API
9. Experience developing & deploying ML models to production ( development, evaluation, validation, deployment & integration to enterprise systems).
Who you are as a person/leader :
1. Owner mentality - For you, the buck stops at you, You own it, you will learn it, and you will get it done
2. You are naturally curious. Always experimenting than hypothesizing - You like to push boundaries, you figure things out and experiment your way through any problem
3. You are passionate, unafraid & loyal to the team & mission
4. You love to learn & win together
5. You communicate well through voice, writing, chat or video, and work well with a remote/global team
Nice to have competencies :
1. Large/Complex organization experience in deploying NLP/ML in production
2. Experience in efficiently scaling ML model training and inferencing
3. Experience with Big Data technologies using Kafka, Spark, Hadoop, Snowflake
Some perks of working with us :
Outsized Bet : We are a young company, funded by early customer traction, and leading VCs, and provides you an opportunity to start at the ground floor. A few years may turn into a plush retirement fund.
1. Learning - Constantly learn from founders, community and customers
2. Startup Perks - Ownership, Autonomy &Mastery
3. Standard Benefits - insurance, commute etc.
4. Paid vacation, benefits and a commitment to everyone's physical/mental health
5. You get to change the way the world, and leave a lasting impact.
We are an equal opportunity employer and do not discriminate on the basis of race, religion, national origin, gender, sexual orientation, age, veteran status, disability, or other legally protected statuses.
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