Machine Learning Engineer (LLM, Prompt engineering)

Alindor Corp. is 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

Alindor 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.

Find more details about us here: https://drive.google.com/drive/u/0/folders/1DYfkks4nF0lXl5wuBKU3piHpJrxZXoe1

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.

Extra hours requirements:

• Willingness to work extended hours and weekends as needed

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.
• Data Preparation and Research: Skilled in quickly sourcing and retrieving training data from diverse sources such as APIs, public data sets like Kaggle, and academic databases.
• Backend Development: Strong in backend technologies and frameworks, including Node.js, Django, Flask, and FastAPI. Experienced in designing RESTful APIs, implementing microservices architecture, and developing server-side logic for scalable applications.
• Frontend Development: Capable of creating user-friendly web platforms independently, using HTML, CSS, JavaScript, and React. Demonstrated UI/UX design skills in developing intuitive interfaces and seamless user experiences.
• Cloud Computing: Cloud services like AWS, Azure, or Google Cloud Platform. Design systems that are scalable and reliable, capable of handling growth in users and data.
• Containerization and Orchestration: Containerization tools like Docker and orchestration systems like Kubernetes for efficient deployment and scaling of applications.
• Database Management: Database technologies such as MySQL, PostgreSQL, MongoDB, or similar.
• Security and Compliance: Awareness of cybersecurity best practices and compliance requirements, particularly in relation to data protection and privacy.
• Version Control and CI/CD: Version control tools such as Git and implementing continuous integration/continuous deployment (CI/CD) pipelines to streamline development and deployment processes.
• Testing and Quality Assurance: Experience in implementing testing frameworks and conducting thorough quality assurance to ensure the backend system’s robustness and reliability.
• Hiring and management: Proficient in talent acquisition and management, with the ability to identify, hire, and effectively lead a team of high-performing engineers.

It’s remote work. Worldwide.

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).

You should join our startup, because you will:

• Have the most interesting experience ever.
• Do something unique, which nobody else does.
• Enhance the quality of the workforce worldwide, thereby contributing to global economic development.
• Be at the forefront of scientific advancements.
• Be part of an elite team.
• Find lifelong friends and maybe life partners.

But it will be:

• Stressful
• Hard
• Tensely

Hiring process

1. Candidate survey (10 minutes to complete)

Candidates, with prospective CV / portfolio, will complete a candidate survey at https://forms.gle/KtcFxKgnfeCsrtGk9. Applicants can also fill out this survey on their own, even if the hiring manager hasn’t asked them to. This can speed up the hiring process or give the applicant an extra chance, especially if he wasn’t initially selected.

2. Screening interview (15 minutes)

Career goals, professional strengths, desires, areas of disinterest, weaknesses, previous supervisors and past performance.

3. Test assignment (few hours)

Candidates who have passed a screening interview, as well as those lacking relevant experience and therefore did not undergo such an interview, will complete a test assignment closely aligned with the actual tasks they would perform in their position within the company. There are no trivial tasks or irrelevant challenges; only real-world assignments are given. We don’t send test assignments to most candidates. If you receive an assignment, it means you are in the top 10% of the best applicants. We are committed to providing feedback for each assignment, regardless of the quality of completed assignment, because we respect time and efforts of each candidate.

If you wish to speed up your hiring process and add trustworthy to your candidacy, you are welcome to complete a test assignment without waiting for a request from the hiring manager. More: https://docs.google.com/document/d/1WM9F5hhixv2ucD8ht7iagrY9pmt3agtk/preview

4. Topgrading Interview (1-3 hours)

Candidate’s experience, notable achievements, challenges faced and relationships with supervisors and colleagues.

5. Focused interview (1-3 hours)

Candidate’s competencies, vision and ideas about our product.

6. Reference interview (without attendance of candidate)

Call with few references, which candidate provided on previous steps. 4-7 references from management, colleagues, subordinates. If a candidate lacks past experience, he can still provide references that can speak to his character, work ethic, or relevant skills. These may include academic, personal, community service, coach, or mentor references. Candidate should help to arrange a meeting (10-15 min) with each of his reference.

7. Offer interview (15 minutes)

Job offer discussion.

ALINDOR focuses on Mobile, Machine Learning, Artificial Intelligence, Psychology, and Big Data Analytics. Their company has offices in Delaware. They have a small team that’s between 1-10 employees.

You can view their website at https://alindor.tech or find them on Twitter and LinkedIn.