The Senior ML/AI Engineer will collaborate with data scientists to implement optimized ML workflows, develop tools for prompt management, and monitor system performance while managing data pipelines and integrating AI APIs.
We are:
Wizeline, a global AI-native technology solutions provider, develops cutting-edge, AI-powered digital products and platforms. We partner with clients to leverage data and AI, accelerating market entry and driving business transformation. As a global community of innovators, we foster a culture of growth, collaboration, and impact.
With the right people and the right ideas, there’s no limit to what we can achieve
Are you a fit?
Sounds awesome, right? Now, let’s make sure you’re a good fit for the role:
Key Responsibilities
- Collaborate with data scientists and engineers to orchestrate LLMs and tools into complex AI workflows.
- Implement optimized vector storage and indexing systems for NLP.
- Develop tools and frameworks for prompt management, automated evaluations, and observability.
- Monitor and improve agentic systems performance for accuracy and efficiency.
- Provide ongoing support, troubleshoot issues, and implement updates for ML solutions
- Build and maintain data processing pipelines for high volumes of structured and unstructured data.
- Integrate third-party AI APIs (internal and external) to extend the functionality of systems.
- Stay updated on GenAI, NLP, ML, and IR technologies, incorporating best practices and leveraging cloud infrastructure for efficiency.
- Build and extend internal products on top of the LangChain ecosystem (LangGraph, LangSmith) to support prompt management, evaluation, and agent orchestration across the team.
Must-have Skills:
- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related STEM field or equivalent work experience.
- 4+ years of industrial experience in a machine learning engineering or data engineering role.
- Strong programming skills in Python and/or another high-level language commonly used in machine learning.
- Experience deploying LLMs, implementing automated evaluation pipelines (LLM-as-a-judge), and architecting multi-agent systems that utilize tool-calling and long-term memory to solve non-linear problems.
Nice-to-have:
- AI Tooling Proficiency: Leverage one or more AI tools to optimize and augment day-to-day work, including drafting, analysis, research, or process automation. Provide recommendations on effective AI use and identify opportunities to streamline workflows.
- Familiarity with cloud-based infrastructure and services (e.g., AWS and GCP), Docker, and the Git version control system
- Familiarity with consuming and integrating APIs in a reliable and secure manner.
What we offer:
- A High-Impact Environment
- Commitment to Professional Development
- Flexible and Collaborative Culture
- Global Opportunities
- Vibrant Community
- Total Rewards
*Specific benefits are determined by the employment type and location.
Find out more about our culture here.
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