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Senior ML Engineer Position
1 week ago
Are you looking for a challenging role that combines cutting-edge technology with collaborative teamwork? Look no further At Applied Textiles, Inc., we are seeking a highly skilled Senior Applied Research Engineer to join our team of experts in machine learning.
In this role, you will be responsible for developing and delivering high-quality solutions using modern software development practices. This includes creating large-scale data processing pipelines and designing scalable ML solutions that drive the company's digital transformation.
About the Role- Develop and Deliver: You will be involved in the entire software development lifecycle, building, testing, and delivering high-quality solutions.
- Build Scalable ML Solutions: You will create large-scale data processing pipelines to help researchers build and train novel machine learning algorithms, and develop high-performing scalable systems in the context of large online delivery environments.
- Collaborate with Cross-Functional Teams: Working in a collaborative team-oriented environment, you will share information, value diverse ideas, partner with cross-functional and remote teams.
- Be an Agile Person: With a strong sense of urgency and a desire to work in a fast-paced, dynamic environment, you will deliver timely solutions.
As a Senior Research Engineer, you will have the opportunity to try new approaches and learn new technologies, contributing innovative ideas, creating solutions, and being accountable for end-to-end deliveries. Effective communication is key, and you will articulate ideas and collaborate on technical developments with cross-functional partners and team members.
We are looking for someone with a Bachelor of Science degree in computer science or a related field, with at least 5 years of software engineering experience, ideally in the context of machine learning and natural language processing. You should have a deep understanding of Python software development stacks and ecosystems, as well as experience with other programming languages and ecosystems.
Able to understand, apply, integrate, and deploy Machine Learning capabilities and techniques into other systems, you should be familiar with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn. Take pride in writing clean, reusable, maintainable, and well-tested code. Have a desire to learn and embrace new and emerging technology.
Familiar with probabilistic models and having an understanding of the mathematical concepts underlying machine learning methods, you should have experience integrating Machine Learning solutions into production-grade software and an understanding of ModelOps and MLOps principles. Demonstrate proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or Azure (or a related cloud platform).
Prior experience with Natural Language Processing (NLP) problems and familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc. Are able to understand and translate between language and methodologies used both in research and engineering fields.
Have been successfully taking and integrating Machine Learning solutions to production-grade software. Hands-on experience in other programming and scripting languages (Java, TypeScript, JavaScript, etc.).
