Lead - ML Engineering - job 1 of 2

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What’s in it for you:

Be part of a global enterprise and build AI solutions at scale.
Work alongside a highly skilled and technically strong team.
Contribute to solving high-complexity, high-impact challenges in data transformation and machine learning.

Responsibilities:

Build production ready data acquisition and transformation pipelines from ideation to deployment.
Being a hands-on problem solver and developer helping to extend and manage the data platforms.
Apply best practices in data modeling and building ETL pipelines (streaming and batch) using cloud-native solutions
Model development: Design, develop, and evaluate state-of-the-art machine learning models for information extraction, leveraging techniques from NLP, computer vision (if applicable), and other relevant domains.
Data preprocessing and feature engineering: Develop robust pipelines for data cleaning, preprocessing, and feature engineering to prepare data for model training.
Model training and evaluation: Train, tune, and evaluate machine learning models, ensuring high accuracy, efficiency, and scalability.
Deployment and monitoring: Deploy and maintain machine learning models in a production environment, monitoring their performance and ensuring their reliability.
Research and innovation: Stay up-to-date with the latest advancements in machine learning and NLP, and explore new techniques and technologies to improve the extraction process.
Collaboration: Work closely with product managers, data scientists, and other engineers to understand project requirements and deliver effective solutions.
Code quality and best practices: Ensure high code quality and adherence to best practices for software development.
Communication: Effectively communicate technical concepts and project updates to both technical and non-technical audiences.

What We’re Looking For:

6-10 years of professional software work experience, with a strong focus on Machine Learning, Natural Language Processing (NLP) for information extraction and MLOps
Expertise in Python and related NLP libraries (e.g., spaCy, NLTK, Transformers, Hugging Face)
Experience with Apache Spark or other distributed computing frameworks for large-scale data processing.
AWS/GCP Cloud expertise, particularly in deploying and scaling ML pipelines for NLP tasks.
Solid understanding of the Machine Learning model lifecycle, including data preprocessing, feature engineering, model training, evaluation, deployment, and monitoring, specifically for information extraction models .
Experience with CI/CD pipelines for ML models, including automated testing and deployment.
Docker & Kubernetes experience for containerization and orchestration.
OOP Design patterns, Test-Driven Development and Enterprise System design
SQL (any variant, bonus if this is a big data variant)
Linux OS (e.g. bash toolset and other utilities)
Version control system experience with Git, GitHub, or Azure DevOps.
Excellent Problem-solving, Code Review and Debugging skills
Software craftsmanship, adherence to Agile principles and taking pride in writing good code
Techniques to communicate change to non-technical people

Nice to have

Core Java 17+, preferably Java 21+, and associated toolchain
Apache Avro
Apache Kafka

Other JVM based languages - e.g. Kotlin, Scala

Average salary estimate

$140000 / YEARLY (est.)

min

max

$120000K

$160000K

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What You Should Know About Lead - ML Engineering, Talent Worx

Join our innovative team as a Lead - ML Engineering and be part of a global enterprise that is building AI solutions at scale! At our company, you’ll have the opportunity to tackle high-complexity, high-impact challenges in data transformation and machine learning. You’ll build production-ready data acquisition and transformation pipelines from ideation to deployment, working in a hands-on capacity to extend and manage our robust data platforms. We expect you to design and develop state-of-the-art machine learning models, applying techniques from NLP and computer vision as relevant. Your responsibilities will include data preprocessing, feature engineering, as well as model training and evaluation to ensure optimum performance and scalability. You’ll also deploy and monitor these models in production while staying updated with the latest advancements in machine learning and NLP technologies. Collaboration is key, so you will work closely with product managers and data scientists, ensuring that project requirements are met with effective solutions. To succeed, you should have 6-10 years of professional experience focused on Machine Learning and MLOps, alongside a strong command of Python and relevant NLP libraries. Experience with cloud platforms such as AWS or GCP, along with familiarity in CI/CD pipelines and containerization, will set you up for success. We believe in maintaining high code quality and practicing agile development principles, and we're excited to see how you can contribute to our mission!

Frequently Asked Questions (FAQs) for Lead - ML Engineering Role at Talent Worx

What are the main responsibilities of the Lead - ML Engineering position?

As the Lead - ML Engineering, your main responsibilities will include building production-ready data acquisition and transformation pipelines, designing and evaluating advanced machine learning models, and collaborating with various teams to deliver effective solutions. You will manage data preprocessing and feature engineering, ensure high accuracy in model training, and maintain deployed models in a production environment.