Software Engineer (ML Team)

Level AI was founded in 2019 and is a Series C startup headquartered in Mountain View, California. Level AI revolutionizes customer engagement by transforming contact centers into strategic assets. Our AI-native platform leverages advanced technologies such as Large Language Models to extract deep insights from customer interactions. By providing actionable intelligence, Level AI empowers organizations to enhance customer experience and drive growth. Consistently updated with the latest AI innovations, Level AI stands as the most adaptive and forward-thinking solution in the industry.

As a critical member of the team, your work will be cutting-edge technologies and will play a high-impact role in shaping the future of AI-driven enterprise applications. You will directly work with people who've worked at Amazon, Facebook, Google, and other technology companies in the world. With Level AI, you will get to have fun, learn new things, and grow along with us.

Position Overview:

As a Machine Learning Engineer, you will play a crucial role in developing, deploying, and maintaining cutting-edge machine learning models across various domains. You will work closely with ML/NLP Engineers, software engineers, and other cross-functional teams to build scalable and high-performance machine learning & NLP solutions that drive business impact.

Competencies:

Python, data structures, algorithms, coding, problem solving, deep learning, machine learning, MLOps, communication

Roles and Responsibilities:

• Big picture: Understand customers' needs and innovate and use cutting-edge Machine Learning techniques to build data-driven solutions.
• Collaborate with cross-functional teams to integrate/upgrade AI solutions into company's products and services. Contribute in achieving high engineering standards across different services.
• Optimize existing machine learning models for performance, scalability, and efficiency.
• Build, deploy, and own scalable production NLP pipelines.
• Build post-deployment monitoring and continual learning capabilities. Propose suitable evaluation metrics and establish benchmarks.
• Keep abreast with SOTA techniques in your area and exchange knowledge with colleagues.
• Suggest impactful improvements and own the post-deployment MLOps service activities completely.
• Contribute in prompt engineering efforts within the team.
• Active participation in bugs identification, resolution, RCA, testing, etc.

We'll love to explore more about you if you have:

• Bachelors in Computer Science or Mathematics related fields with 2-3 years of experience in Machine Learning, NLP, and Software Engineering.
• Proficient in Python and SQL.
• Knowledge of basic Data Structures and Algorithms, and proficient in coding.
• Knowledge and experience with data engineering, basic machine learning concepts, data mining, feature extraction, pattern recognition, etc.
• Knowledge and experience with dashboards, monitoring and logging tools like Datadog, Grafana, etc.
• Basic understanding of NLP problems such as text classification, entity tagging, information retrieval, question-answering, natural language generation, clustering, etc.
• Basic knowledge and hands-on experience with Transformer-based Language Models like BERT, DeBERTa, Flan-T5, GPT, Llama, etc.
• Experience with Deep Learning frameworks like Pytorch and common machine learning libraries like scikit-learn, numpy, pandas, NLTK, etc.
• Experience with prompt engineering and streamlining related processes.
• Experience in following clean, elegant, modular, bug-free coding practices in languages like Python.
• Experience with ML model deployments using REST API, Docker, Jenkins, Helm, Kubernetes, etc.
• Knowledge of cloud platforms (AWS/Azure/GCP) and their machine learning services is desirable.
• Knowledge of real-time streaming tools/architectures like Kafka, Pub/Sub is a plus.