Machine Learning Engineer in startup (full-time)

Machine Learning Engineer (LLM, Prompt engineering) $12k – $80k • 0.5% – 3.0% in stock options Full job description (here is not full, because there is limitation on characters): [login to view URL] We a tech startup based in Delaware, US. We are developing an AI-powered recruiting platform that analyzes and screens candidates' resumes, enabling recruiters to quickly identify top talent while significantly reducing manual screening time and bias. The WHO: Target Audience The main user of our platform is a professional who needs to streamline their recruitment process, particularly in the scope of CV screening and filtering. This allows them to improve the quality of hires and reduce time spent on manual screening. Our primary target customers include recruitment agencies, HR departments of large corporations, and small to medium enterprises. The WHAT: Product offers advanced AI-powered analytics to screen and filter the resumes of job applicants. It goes beyond simple parsing and keyword matching. The platform employs LLMs to process resumes and draw conclusions about the alignment between job requirements and candidates' resumes. The WHY: Mission Our mission is to improve the quality of the workforce worldwide. With our platform, good employees will get hired faster and with less likelihood of facing bias, discrimination, or errors from human recruiters. Less suitable candidates will be identified early, encouraging them to gain additional experience, education, and develop specific aptitudes and skills if they wish to pursue particular job opportunities. We are looking for: Machine Learning Engineer Mission: The mission of the Machine Learning Engineer is to develop, deploy, and maintain a user-friendly and efficient web app for a CV screening solution based on large language models (LLMs). This system should ensure precise AI results and foster organic growth among users. Outcomes: - For 1 week: Create an MVP and launch it in production. The MVP will offer core functionality where a user uploads a candidate's CV and job description, and in return, the user receives a score to decide whether to proceed with the candidate. For the MVP, utilize the OpenAI API, apply proper prompt engineering, and deploy on cloud platforms such as GCP, AWS, etc. - For the next 1 month: Prepare training data, train a custom machine learning model, and improve the quality of CV screening. Additionally, add extra features to the web app for a paid subscription, including account history and other basic functionalities for users—recruiters. - For the next 1 month: Enhance the model, maintain the web app, and address user feedback to achieve 100 active users. - For the next 3 months: Continue to refine the model and scale up rapidly to achieve the processing of 1 million CVs per month. - For the next 1 year: Accelerate scaling by increasing and managing a team of 3-6 ML engineers to ensure the achievement of processing 10 million CVs per month. Personal traits: Interest in our HR/recruitment app and passion for hiring-related products. Respect and Commitment: Adhere to company hierarchy, respect leadership, dedicated to our mission. Independence: Capable of solo work, decision-making, and risk-taking. Positive Attitude: Emotionally stable, solution-focused, resilient to personal issues. Efficiency: Prioritizes effectively, aims for quick and quality outcomes. Team Harmony: Treats colleagues like friends, resolves conflicts independently. Innovation: Proactively proposes and demonstrates new ideas, embraces all tasks. Attention to Detail: Thorough in tasks and testing, prioritizes accuracy. Openness to Feedback (criticism). Global Mindset: Dedicated to societal betterment over personal gains. Personal Growth: Values self-improvement, avoids counterproductive habits. Competencies: Programming and System Design: Proficient in Python and Java, with extensive experience using ML libraries for NLP such as TensorFlow, PyTorch, and spaCy. Natural Language Processing (NLP): Expertise in GPT models (using OpenAI API), Large Language Models (LLMs), prompt engineering, and text preprocessing techniques like tokenization, stemming, and lemmatization. Extra hours requirements: Willingness to work extended hours and weekends as needed Compensation 12000 - 80000 $ a year + 0.5 - 3% stock options Priority will be given to candidates willing to accept a compensation package primarily composed of stock options, accompanied by a modest salary Additional benefits Health insurance Employee referral program: For every referral who is successfully hired and remains with the company for at least six months, you will receive a bonus equivalent to 1-3 months of their salary (depends on position).