About Vailent & Vinmar
Vinmar is a global leader in the marketing and distribution of polymers and chemicals, operating in over 100 countries with more than 45 years of success.
Vailent is a subsidiary of Vinmar, created to reimagine how polymers are bought and sold. We’re building a technology-enabled B2B marketplace that gives buyers and sellers a faster, more transparent, and more efficient way to do business. Our platform is designed to empower Vinmar’s global network while transforming an industry that has seen little digital innovation.
About the Role
At Vailent, you’ll join a small, agile, and fully remote team with the backing and stability of a global parent company. We combine the autonomy of a startup with the reach of a world leader. You’ll find the freedom to own your work, the support of approachable leadership, and the opportunity to solve complex challenges that directly impact how an entire industry operates.
As a Lead AI Engineer, you’ll step into a leadership role, taking ownership of the technical vision for AI across our products and platform. You’ll lead the design, development, and deployment of advanced AI systems, setting architecture, practices, and standards that ensure solutions are scalable, production-ready, and deeply embedded in our product strategy. Beyond hands-on engineering, you’ll mentor other developers, guide cross-functional teams, and drive adoption of best practices. With access to state-of-the-art infrastructure and AI/ML tools, you’ll architect large-scale solutions and collaborate with product, engineering, and business leaders to shape the future of AI innovation across the company.
Why Join Us
- A culture that values technical excellence, ownership, and innovation.
- High impact, real ownership — Your work directly shapes the future of a global industry.
- Autonomy & trust — Freedom to own projects and make decisions.
- Team & culture — A collaborative environment where leadership is accessible, and people genuinely enjoy working together.
- Growth & learning — Opportunities to learn new skills, take on big challenges, and grow with a company on the rise.
- Flexibility — Remote-first culture with balance built in.
- Competitive compensation — Salary, benefits, and support for professional development.
What You’ll Do
- Define the technical strategy and roadmap for AI initiatives across the organization.
- Architect and implement large-scale AI/ML systems that meet performance, reliability, and security requirements.
- Lead integration of LLMs, generative AI, and ML models into customer-facing applications and internal platforms.
- Oversee the end-to-end AI lifecycle: data engineering, model training, deployment, monitoring, and continuous improvement.
- Guide teams in leveraging cloud infrastructure (AWS SageMaker, EC2 GPU, Lambda, RDS, S3) to scale AI workloads.
- Establish MLOps best practices, including CI/CD pipelines for models, monitoring, and governance.
- Collaborate with executives and stakeholders to align AI solutions with business goals and product vision.
- Mentor and coach engineers across levels, raising the bar for AI/ML knowledge and engineering excellence.
- Stay ahead of emerging AI trends (LLMs, multimodal models, vector databases, retrieval systems) and evaluate applicability.
Hard Skills
- AI/ML Expertise: Deep hands-on experience with modern LLM architectures.
- Systems Architecture: Proven track record designing and deploying production AI systems at scale.
- Programming: Strong in Python, etc. for AI/ML; working knowledge of Java/Spring Boot for enterprise integration.
- Cloud Infrastructure: Advanced experience with AWS AI/ML stack (SageMaker, Lambda, GPU/EC2, RDS, CloudWatch).
- MLOps & CI/CD: Skilled with GitHub Actions, Docker, Kubernetes, and automated AI deployment/monitoring pipelines.
- Data Systems: Expertise in SQL/NoSQL, data pipelines, feature stores, and vector databases (e.g., Pinecone, Weaviate, FAISS).
Soft Skills
- Strong leadership and ability to influence technical direction across engineering teams.
- Excellent communicator who can bridge technical and business discussions.
- Resourceful, independent thinker with a “figure it out” mindset, able to navigate ambiguity and drive clarity.
- Deep sense of ownership, accountability, and ability to set standards and enforce best practices.
- Skilled at mentoring and developing engineering talent.
- Experienced in Agile/Kanban environments, with an emphasis on scaling processes for AI work.
Preferred
- Master’s or PhD in Computer Science, AI/ML, Data Science, or related field.
- Research or production experience with large language models, RAG (retrieval-augmented generation), and generative AI systems.
- Knowledge of responsible AI practices: model fairness, bias mitigation, explainability, and compliance.
- Track record of leading AI strategy and delivering measurable business impact.
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