VPP-58 - ML Engineer

VPP-58 – ML Engineer

We are seeking an LM Engineer to design, fine-tune, and deploy production-grade language model systems. This role focuses on adapting large language models to real-world use cases, optimizing RAG architectures, and ensuring models perform reliably, efficiently, and safely at scale

Department:
AI, Insights, & Solutions
Project Location(s):
India/South America - Remote
Job Type:
Employee
Education:
Bachelor's

Who You’ll Work With

You will be part of a collaborative team that values technical expertise and innovation, working closely with colleagues to create effective AI solutions that drive business value

What You’ll Do

• 3+ years of experience in Python engineering with deep knowledge of ML frameworks (PyTorch/TensorFlow) and LLM libraries (LangChain/LlamaIndex)
• Hands-on experience with API development (FastAPI/Flask) and vector databases like Pinecone or Weaviate
• A strong background in AWS infrastructure, specifically for deploying and scaling containerized ML models
• A solid understanding of NLP, transformers, and traditional data science workflows (feature engineering, cross-validation)
• The ability to communicate complex technical architectures to stakeholders and a leadership mindset to drive AI projects forward in an Agile environment

What You’ll Bring

• Develop and refine AI pipelines by writing modular Python code, focusing on Retrieval-Augmented Generation (RAG) and document processing
• Own the technical decisions regarding model serving architecture, choosing between different AWS services (like SageMaker or Lambda) to balance cost and performance
• Analyze model outputs to identify hallucinations or inefficiencies, applying fine-tuning or re-ranking strategies to improve response relevance
• Maintain the health of production models by monitoring performance metrics and implementing CI/CD pipelines for automated model retraining and deployment
• Act as a core contributor to the team by resolving technical roadblocks in data indexing and API integration

Nice-to-Haves

• Experience with model compression techniques such as pruning, 4-bit/8-bit quantization, or LoRA/QLoRA fine-tuning
• Familiarity with graph databases (Neo4j) or specialized search engines (ElasticSearch) to augment RAG pipelines
• AWS Certified Machine Learning – Specialty or similar cloud/AI certifications
• Contributions to LLM or ML open-source projects
• Experience setting up advanced observability specifically for Generative AI (e
• Arize Phoenix or LangSmith)

What Makes Us Great Place To Work

Vekend is a people-first organization focused on developing thoughtful products and services that create meaningful impact for our customers and communities. We are committed to fostering a collaborative, respectful, and inclusive work environment where employees are empowered to take ownership of their work, contribute ideas, and grow professionally. We strive to support flexibility and work-life balance while maintaining high standards of performance and accountability.

What Makes Us Great Place To Work

For all locations, the good-faith, reasonable annualized full-time compensation for this role will be determined based on competitive market data and may vary depending on geographic location, job-related knowledge, skills, experience, education, and other business considerations. Specific compensation details will be discussed during the interview process.,Vekend offers a comprehensive benefits and wellness package designed to support employees’ overall well-being, financial security, and professional growth. Eligibility and coverage are subject to the terms of the applicable benefit plans and company policies.,Eligible employees have access to medical, dental, and vision insurance with company contributions toward premiums, a 401(k) retirement plan with company matching, and Paid Time Off that begins accruing on the first day of employment. We also support flexible work arrangements and opportunities for professional growth.,Benefits eligibility, coverage, and company contributions are subject to the terms of the applicable plan documents and may be modified at the company’s discretion.

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