Machine Learning Engineer

About Us

Black Ore is building the leading AI platform for financial services. By combining LLMs, proprietary AI/ML and automation we accelerate core workflows for the industry, allow financial services professionals to be more productive and enable consumers to enhance their personal finance. Our flagship product, Tax Autopilot, combines AI with federal and state tax codes & regulations to simplify the tax preparation and review process for Certified Public Accountants (CPAs) and accounting firms.

Founded in 2022, we launched with $60 million in early stage funding from some of the world’s leading investors including a16z, Founders Fund, General Catalyst, Khosla Ventures, Oak HC/FT, Trust Ventures and leading tech founders/angel investors including Jason Gardner (Founder and CEO of Marqeta), Max Levchin (Founder of Paypal and Affirm), Tom Glocer (Former CEO of Thomson Reuters), Gokul Rajaram, and Mark Britto (EVP, CPO, PayPal).

Our team has an incredibly ambitious vision to completely transform the way businesses and consumers interact in financial services. We’re looking to hire strong team members to grow the team. Some of the traits we look for are:

• Owner Mentality - Desire to take initiative, identify problems and implement solutions
• Mission Driven - Passion for building AI/ML solutions that reimagine how businesses and consumers operate
• Intellectually Curious - Excitement going deep and building detailed understanding of the function, role, customer and problem space
• Team Oriented - Ability to collaborate respectfully and put the team above the self

The Role

We are seeking a skilled and driven Senior Machine Learning Engineer with 5+ years of industry experience to join our team. You’ll play a key role in building and deploying machine learning models and AI systems that are reliable, scalable, and impactful. The ideal candidate has experience applying ML techniques in production environments and thrives in a fast-paced, collaborative setting. You will be an expert in Document Extraction and Classification, and also have direct working experience in Prompt Engineering.

*The emphasis of this role is Document Extraction and Document Classification; this experience is required in order to be considered

Responsibilities

• Specialize in Document Extraction and Document Classification
• Design, develop, and deploy machine learning models and AI systems to solve practical problems
• Collaborate with data scientists, software engineers, and product managers to translate research and business goals into deployed solutions
• Evaluate model performance using appropriate metrics and conduct error analysis to identify areas for improvement
• Build data pipelines and model-serving infrastructure for scalable AI solutions
• Stay current with the latest AI/ML techniques and technologies, and evaluate their potential application to our work
• Monitor, maintain, and iterate on models post-deployment to ensure continued performance and value

Basic Qualifications

• Master's degree in Computer Science, Engineering, Data Science, or a related field;
• 5+ years of industry experience in Applied Machine Learning or AI engineering
• 3+ years of recent industry experience in Document Extraction and Document Classification
• Direct experience in Prompt Engineering
• Continued interest in LLM trends and the latest in cutting edge models within AI
• Proficient in Python and ML libraries such as TensorFlow, PyTorch, scikit-learn, or similar
• Strong understanding of ML fundamentals, including supervised/unsupervised learning, model evaluation, feature engineering, and overfitting/underfitting
• Experience working with large datasets and building production-ready data pipelines (e.g., with Spark, Airflow, or similar tools)

Preferred Qualifications

• Knowledge of Machine Learning best practices and tools
• Experience contributing to research or working on experimental ML projects
• Comfort working in agile teams with cross-functional collaboration

What We Offer (for U.S. Based Employees)

• Competitive salary and equity based compensation
• Employer-paid medical, dental and vision insurance
• Ability to define your own success
• Continuous learning and new challenges to master