Machine Learning Engineer

We are looking for an experienced Applied Machine Learning Engineer to join our globally-distributed Data Engineering team. With deep expertise in Python and a passion for building scalable ML solutions, you’ll have the opportunity to work on high impact projects using cutting-edge ML technologies. You’ll work with large, complex datasets, developing advanced applications, including those involving Large Language Models (LLMs). A key part of this role will be owning the implementation of brand new ML services for additional data points we aim to develop. This role offers significant opportunities for growth and advancement as you address a wide variety of challenging problem sets. This is a full-time, contract, role that reports directly to our Director of Engineering, Data.

About us 
At Sourcescrub, we are an innovative, data-driven company focused on delivering impactful machine learning applications at scale. We believe two areas of focus are paramount to modern deal origination: Exceptional data quality and a relentless approach to Business Development. Our innovative approach allows finance professionals at all levels in their organization to find, research, track, and connect with privately-held companies. 

About you 

You are an experienced ML engineer with advanced Python skills, capable of designing, implementing, and scaling ML solutions. You thrive in collaborative environments, working across teams to deliver reliable, high-quality solutions that meet business needs and ensure data integrity at every stage.

As our Machine Learning Engineer, you will

• Develop and maintain ML models with a focus on scalability, especially for deploying and optimizing LLMs in production environments
• Collaborate with cross-functional teams to deliver end-to-end ML solutions, from data preprocessing to model deployment
• Implement data preprocessing, feature engineering, and model evaluation processes to ensure the highest standards of accuracy and efficiency
• Develop and manage ML pipelines in Python for performance at scale
• Leverage cloud platforms (e.g., Azure, AWS) for deploying, scaling, and monitoring models in production
• Stay current with advancements in LLMs, ML frameworks, and Python development best practices

To be successful, you should have 

• 3+ years of proven experience as an Applied ML Engineer or similar role, with a focus on Python 
• 3+ years of advanced Python skills, with strong experience in libraries such as Pandas, NumPy, TensorFlow, PyTorch, and Scikit-Learn
• Demonstrated experience in deploying and optimizing ML models at scale, with knowledge of LLMs and other scalable architectures
• 3+ years of strong knowledge of SQL and database management for data storage and retrieval 
• 2+ years of experience with version control, particularly Git 
• Strong analytical, problem-solving, and attention to detail skills
• Excellent communication and teamwork, particularly in agile environments

Nice to have

• Experience with web scraping frameworks such as Scrapy and BeautifulSoup for data extraction and preprocessing
• Familiarity with ML Ops tools and practices for streamlined model lifecycle management
• Experience with data engineering tools to support robust ML pipelines
• Background in NLP, computer vision, or time-series forecasting, especially with large-scale data
  

Sourcescrub does not accept unsolicited resumes from search firm recruiters. Fees will not be paid in the event a candidate submitted by a recruiter without an agreement in place is hired; such resumes will be deemed the sole property of Sourcescrub.