Machine Learning Engineer

J-VERS is a programmatic job advertising agency that helps employers find the right candidates in any industry by optimizing the hiring process. Founded in 2023, the company has grown 5x, building a fully remote team that serves over 150 enterprise clients across the US and EU through AI-powered advertising technology.

About the product

We are an innovative programmatic job advertising startup building intelligent solutions that optimize recruitment marketing campaigns. Our mission is to leverage cutting-edge machine learning and AI to maximize campaign efficiency and improve hiring outcomes at scale. We've recently finished the MVP stage and are now scaling the product. A great chance to join a small startup team (CTO, 4 Developers, QA Developer, DevOps Engineer, and Product Owner), and have a real impact on its development

Technical stack: Python 3.11+, FastAPI, Postgres, Kafka, Kubernetes; TypeScript, React; AWS.

What You'll Be Doing:

• Design, build, test, and deploy ML models that automate and optimize campaign performance;
• Develop and maintain scalable ML pipelines, ensuring reliability and performance in production;
• Integrate LLMs into our existing platform to enable intelligent features such as CV pre-screening and automated marketing content generation;
• Research, design, and adapt ML algorithms to address business-specific challenges in recruitment advertising;
• Collaborate with product and engineering teams to integrate AI services into production systems;
• Experiment with reinforcement learning approaches to dynamically tune and optimize campaign performance;
• Continuously improve models and pipelines with monitoring, retraining, and evaluation workflows.

Your Skills:

• Strong background in Python and ML libraries (TensorFlow or PyTorch, Scikit-learn, pandas);
• Hands-on experience with classic ML algorithms (classification, regression, clustering) as well as deep learning architectures;
• Familiarity with LLMs, prompt engineering;
• Experience building production-ready ML pipelines;
• Strong skills in Docker and AWS for deployment and scaling;
• Knowledge of reinforcement learning techniques (advantage);
• Ability to conduct applied research and adapt state-of-the-art models to real-world problems;
• Strong problem-solving and communication skills, comfortable working in a fast-moving startup environment.

Will be a plus:

• NLP fundamentals;
• Knowledge of MLOps frameworks (e.g., MLflow, Kubeflow, SageMaker).

Key Projects You'll Work On:

• LLM-powered CV prescreening service to automate candidate shortlisting;
• Automated marketing campaign generator;
• Reinforcement learning engine to dynamically optimize campaign spend and performance in real time.

You'll thrive at J-Vers if you:

• Self-motivated and comfortable with autonomy;
• Passionate about using technology to solve real problems;
• Open to collaboration and knowledge sharing;
• Results-oriented and focused on impact;
• Curious and committed to continuous learning.

Why Join Us:

Work Without Limits:

• Remote-first team with no location limits;
• Flexible 8-hour workday;
• Flat structure with direct access to leadership;
• Full set of equipment provided for your comfortable work.

Get Rewarded & Supported:

• Competitive compensation with transparent salary bands;
• Health insurance after 3 months of work;
• Mental health support;
• 24 vacation days + 20 paid sick days + 4 no-doc sick days + company-wide one-week break at year-end.

Endless Opportunities to Grow:

• Personal learning budget for professional development;
• Clear growth paths from Junior to Senior;
• Work with global clients (US & EU);
• Culture of feedback, mentorship, and constant learning.

Hiring Process:

• Intro call with a recruiter
• Values-based interview
• Technical interview
• Final interview with CTO
• Recommendation

At J-Vers, you're not just filling a job — you're joining a mission. We're building something extraordinary where technology and humanity combine to transform hiring. Flex your skills. Expand your impact. Shape the future of global hiring.

Read more about us on Happy Monday )

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