About Project

Provectus helps companies adopt ML/AI to transform the ways they operate, compete, and drive value. The focus of the company is on building ML Infrastructure to drive end-to-end AI transformations, assisting businesses in adopting the right AI use cases, and scaling their AI initiatives organization-wide in such industries as Healthcare & Life Sciences, Retail & CPG, Media & Entertainment, Manufacturing, and Internet businesses.

Asan ML Engineer, you’ll beprovided with all opportunities for development and growth.

Let's work together to build a better future for everyone!

Responsibilities

- Technical Delivery (60%)
- Design and implement end-to-end ML solutions from experimentation to production;
- Build scalable ML pipelines and infrastructure;
- Optimize model performance, efficiency, and reliability;
- Write clean, maintainable, production-quality code;
- Conduct rigorous experimentation and model evaluation;
- Troubleshoot and resolve complex technical challenges.

- Collaboration and Contribution (25%)

- Mentor junior and mid-level ML engineers;
- Conduct code reviews and provide constructive feedback;
- Share knowledge through documentation, presentations, and workshops;
- Collaborate with cross-functional teams (DevOps, Data Engineering, SAs);

- Innovation and Growth (15%)

- Stay current with ML research and emerging technologies;
- Propose improvements to existing solutions and processes;
- Contribute to the development of reusable ML accelerators;
- Participate in technical discussions and architectural decisions.

Requirements

- ML Fundamentals: supervised, unsupervised, and reinforcement learning;
- Model Development: feature engineering, model training, evaluation, hyperparameter tuning, and validation;
- ML Frameworks: classical ML libraries, TensorFlow, PyTorch, or similar frameworks;
- LLMs and Generative AI
- LLM Applications: Experience building production LLM-based applications;
- Prompt Engineering: Ability to design effective prompts and chain-of-thought strategies;




- RAG Systems: Experience building retrieval-augmented generation architectures;
- Vector Databases: Familiarity with embedding models and vector search;
- LLM Evaluation: Experience with evaluation metrics and techniques for LLM outputs.

- Data and Programming

- Python: Advanced proficiency in Python for ML applications;
- Data Manipulation: Expert with pandas, numpy, and data processing libraries;
- SQL: Ability to work with structured data and databases;
- Data Pipelines: Experience building ETL/ELT pipelines- Big Data: Experience with Spark or similar distributed computing frameworks.

- MLOps and Production

- Model Deployment: Experience deploying ML models to production environments;
- Containerization: Proficiency with Docker and container orchestration;
- CI/CD: Understanding of continuous integration and deployment for ML;
- Monitoring: Experience with model monitoring and observability;
- Experiment Tracking: Familiarity with MLflow, Weights and Biases, or similar tools.

- Cloud and Infrastructure

- AWS Services: Strong experience with AWS ML services (SageMaker, Lambda, etc.);
- GCP Expertise: Advanced knowledge of GCP ML and data services;
- Cloud Architecture: Understanding of cloud-native ML architectures;
- Infrastructure as Code: Experience with Terraform, CloudFormation, or similar.

Will be a plus

- Practical experience with cloud platforms (AWS stack is preferred, e.g. Amazon SageMaker, ECR, EMR, S3, AWS Lambda);
- Practical experience with deep learning models;
- Experience with taxonomies or ontologies;
- Practical experience with machine learning pipelines to orchestrate complicated workflows;
- Practical experience with Spark/Dask, Great Expectations.

What We Offer

- Fully remote setup;
- A budget for your medical insurance;
- Paid sick leave, vacation, public holidays;
- Continuous learning support, including unlimited AWS certification sponsorship.

Interview stages

- Recruitment Interview;
- HR Interview;
- HM Interview.

We are waiting for you to become a part of our team!

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📌 Senior ML Engineer (GenAI) (Metropolitana)
🏢 Provectus IT
📍 Metropolitana