Proxify is seeking a senior-level Machine Learning Engineer to spearhead the AI strategy and architecture for one of our clients. This role involves building a robust, production-grade AI engine that drives core business value. Key requirements include proven experience in building and deploying ML models, expertise in working with Large Language Models, and strong proficiency in building agentic workflows.
Key Highlights
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
About us:
Talent has no borders. Proxify's mission is to connect top developers around the world with the opportunities they deserve. So, it doesn't matter where you are; we are here to help you fast-track your independent career in the right direction.
Since our launch, Proxify's developers have successfully worked with 1200+ happy clients to build their products and growth features. 5000+ talented developers trust Proxify and its network to fulfill their dreams and objectives.
Proxify is shaped by a global network of supportive, talented developers interested in remote full-time jobs. Our Glassdoor (4.5/5) and Trustpilot (4.8/5) ratings reflect the trust developers place in us and our commitment to our members' success.
The Role:
We are looking for a senior-level Machine Learning Engineer to spearhead the AI strategy and architecture for one of our clients. This is a pivotal leadership role designed for an engineer who can move beyond basic API integrations to build a robust, production-grade AI engine that drives core business value.
What we are looking for:
- Machine Learning Engineering: Proven experience building and deploying ML models in a production environment, specifically focused on Natural Language Processing (NLP) or Recommendation Systems.
- Advanced LLM Implementation: Deep expertise in working with Large Language Models (e.g., GPT-4, Llama 3) beyond simple API calls, including context window management and cost optimization.
- Agentic Frameworks & RAG: Strong proficiency in building agentic workflows and implementing retrieval mechanisms (e.g., Vector Databases, SQL-aware AI agents).
- Software Engineering: Strong Python skills and the ability to work within a backend ecosystem to ensure AI features are scalable and stable.
- Strategic Ownership: Ability to translate client needs into a technical roadmap and defend architectural choices to stakeholders.
- Intermediate-advanced English level.
- Time zone: CET (+/- 3 hours). We are unable to consider applications from candidates in other time zones.
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Nice-to-Have Skills:
- Specialized Fine-Tuning: Experience in fine-tuning open-source models for niche industry domains.
- Data Science Foundations: Background in data cleaning, preprocessing, and exploratory data analysis to support custom model training.
- Geographical Preference: Candidates located within European time zones or those open to future relocation to Berlin.
Responsibilities:
- Architectural Leadership: Act as the primary technical authority for AI/ML decisions, selecting appropriate models (LLMs, SLMs) and frameworks based on specific business use cases.
- Roadmap Execution: Lead the transition from generic model utilization to sophisticated, data-integrated architectures, targeting custom fine-tuning by mid-2024.
- System Integration: Design and implement agentic workflows and RAG (Retrieval-Augmented Generation) systems that interface seamlessly with existing backend services.
- Performance Optimization: Advance beyond basic prompt engineering to improve model accuracy, reliability, and responsiveness for client-facing matching algorithms.
- Mentorship & Best Practices: Establish high standards for AI development within the engineering team, providing guidance on "production-grade" AI implementation versus prototyping.
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What we offer:
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