Founding Engineer - California, United States - modCounsel

Description

About the Company

modCounsel provides targeted technology to improve the value and impact of modern legal teams. With advanced data processing and collective intelligence, legal teams make their existing resources more productive and fundamentally improve the quality of decision making especially as business demand scales. Effective risk management requires clarity that technology can bring to expert fingertips when legal judgment is being applied. From contract review, to corporate and regulatory, or transformation projects in legal operations, modCounsel delivers solutions to its clients from day one. We are a minority owned and operated company seeking talent who shares our commitment to creating a more effective and healthier work environment in legal for everyone.

Our Ideal Candidate

As our Chief Technology Officer, you are a first principles thinker with a vision to improve the way humans work in traditional markets using technology. As you learn customer pain points, you question existing solutions and processes with the raw intelligence you bring in machine learning, data engineering, and data science. You accept that solutions are best designed with input from others under a common goal and enjoy facilitating learning loops with technical and non-technical audiences. As a rising star in your field, you have a proven track record in developing and refining Small Language Models (SLMs), a strong background in data engineering, and notable achievements in crafting predictive models from scratch. You thrive in a fast-paced startup environment with a lean team and wear multiple hats to help modCounsel adapt quickly to changing priorities.

How You Will Make Your Impact

• Technical Expertise: Apply skills in machine learning, data engineering, and data science to process language and build predictive models.
• Machine Learning Leadership: Develop internal processes from design to build and optimize Small Language Model (SLM) for prediction and reinforcement learning with a proprietary data set.
• Data Engineering Management: Design detailed data pipelines and infrastructure, ensuring our ML and RAG projects are scalable, efficient, and robust.
• Data Science Direction: Lead data science projects from concept to deployment, using statistical modeling and machine learning to generate actionable insights.
• ML Ops Development: Establish a comprehensive ML Ops platform for efficient model deployment, monitoring, and management.
• Collaboration and Strategy: Work across departments to align tech strategies with business requirements, fostering an innovative and efficient culture.
• Stakeholder Engagement: Communicate with internal and external stakeholders to meet their technological needs and expectations.
• Risk and Quality Management: Identify tech risks and establish security protocols while setting quality standards for technology systems.

Attributes of Success in this Role

• Proven experience leading technology strategies with a focus on machine learning, data engineering, and data science.
• Demonstrated expertise in developing data technology solutions from concept to launch
• Strong analytical and problem-solving abilities, capable of addressing complex challenges with innovative solutions.
• Solid understanding of industry-specific technologies and trends that affect the organization's operations and strategic direction.
• Excellent leadership and team-building skills, with a track record of mentoring and guiding teams to success.
• Effective communication skills, adept at conveying complex technical concepts to non-technical stakeholders.

Minimum Requirements

• Advanced degree in Applied Science, Computer Engineering, Computer Science, Data Science, or related field.
• 5 years of progressive experience in technology roles, with proven experience in leading technology solutions from 0 to 1.
• Extensive experience in machine learning, particularly with developing and fine-tuning small language models.
• Knowledge of various data technology platforms and data management tools including their deployment and management in an enterprise setting.
• Proven expertise in building technology solutions for B2B clients.
• Strong foundation in data engineering, including the architecture of large-scale data pipelines, management, and maintenance.
• Demonstrated success in data science, including experience with statistical modeling, machine learning algorithms, and preferably with predictive model development.
• Proven leadership experience in a fast-paced startup environment.
• Experience in establishing and managing ML Ops platforms is preferred.

Location: San Francisco - Remote

Reports to: Founder, CEO