The job, in the employer's words
About Scalepex
Scalepex is a nearshore partner that empowers businesses to scale efficiently and effectively through exceptional services. With a strong focus on customer success, innovation, and cultural alignment, we support companies in building high-performing teams across industries.
At Scalepex, we believe in fostering an environment where our people can thrive, grow their careers, and make a real impact.
Role Overview
What You’ll Do
- Start by building foundational AI capabilities and products, with opportunities to grow into leading teams and larger initiatives as they scale
- Lead the design and development of end-to-end AI applications — from prototype to production
- Work closely with founders, clients, and other engineers to shape both technical and product direction
- Build and deploy LLM-based systems, including RAG pipelines, fine-tuned models, and embedding search
- Own delivery of real-world solutions: architect, implement, test, ship
- Iterate rapidly: explore new tools, try new ideas, and solve problems creatively
- Operate with autonomy in a fast-changing environment — sometimes as the only engineer on a project
- Occasionally dive into adjacent areas like frontend, dev tooling, or data pipelines as needed
Requirements
Must-Have Skills
- Strong experience with modern AI techniques — LLMs, prompting, fine-tuning, RAG, vector databases
- Strong Python engineering background, with clean, modular coding practices
- Comfortable building systems in a solo or small-team setting with limited structure
- Familiarity with cloud deployment (AWS/GCP), Docker, and production ML pipelines
- Able to balance product thinking and engineering discipline
- Startup mentality: comfortable with ambiguity, fast iteration, and wearing many hats
- Excellent communication skills — able to work directly with clients and non-technical stakeholders
Bonus Skills
- Experience in Conversational AI and Voice AI systems
- Knowledge of ML frameworks (PyTorch, scikit-learn, etc.)
- Exposure to frontend (JS/React) or dev tooling is a plus
- MLOps / CI/CD familiarity
Benefits
- Contractor scheme
- 100% Remote
Benefits mentioned
- Contractor scheme
- 100% Remote
Requirements mentioned
- Strong experience with modern AI techniques — LLMs, prompting, fine-tuning, RAG, vector databases
- Strong Python engineering background, with clean, modular coding practices
- Comfortable building systems in a solo or small-team setting with limited structure
- Familiarity with cloud deployment (AWS/GCP), Docker, and production ML pipelines
- Able to balance product thinking and engineering discipline
- Startup mentality: comfortable with ambiguity, fast iteration, and wearing many hats
- Excellent communication skills — able to work directly with clients and non-technical stakeholders
- Experience in Conversational AI and Voice AI systems
- Knowledge of ML frameworks (PyTorch, scikit-learn, etc.)
- Exposure to frontend (JS/React) or dev tooling is a plus
- MLOps / CI/CD familiarity
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