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.