Zolvit is looking for a highly skilled and self-driven Lead Machine Learning Engineer / Lead Data Scientist to lead the design and development of scalable, production-grade ML systems. This role is ideal for someone who thrives on solving complex problems using data, is deeply passionate about machine learning, and has a strong understanding of both classical techniques and modern AI systems like Large Language Models (LLMs).

You will work closely with engineering, product, and business teams to identify impactful ML use cases, build data pipelines, design training workflows, and ensure the deployment of robust, high-performance models at scale.

Key Responsibilities:

● Design and implement scalable ML systems, from experimentation to deployment.

● Build and maintain end-to-end data pipelines for data ingestion, preprocessing, feature engineering, and monitoring.

● Lead the development and deployment of ML models across a variety of use cases — including classical ML and LLM-based applications like summarization, classification, document understanding, and more.

● Define model training and evaluation pipelines, ensuring reproducibility and performance tracking.

● Apply statistical methods to interpret data, validate assumptions, and inform modeling decisions.

● Collaborate cross-functionally with engineers, data analysts, and product managers to solve high-impact business problems using ML.

● Ensure proper MLOps practices are in place for model versioning, monitoring, retraining, and performance management.

● Keep up-to-date with the latest advancements in AI/ML, and actively evaluate and incorporate LLM capabilities and frameworks into solutions.

● Mentor junior ML engineers and data scientists, and help scale the ML function across the organization.

Required Qualifications:

● 7+ years of hands-on experience in ML/AI, building real-world ML systems at scale.

● Proven experience with classical ML algorithms (e.g., regression, classification,

clustering, ensemble models).

● Deep expertise in modern LLM frameworks (e.g., OpenAI, HuggingFace, LangChain)

and their integration into production workflows.

● Strong experience with Python, and frameworks such as Scikit-learn, TensorFlow,

PyTorch, or equivalent.

● Solid background in statistics and the ability to apply statistical thinking to real-world

problems.

● Experience with data engineering tools and platforms (e.g., Spark, Airflow, SQL,

Pandas, AWS Glue, etc.).

● Familiarity with cloud services (AWS preferred) and containerization tools (Docker,

Kubernetes) is a plus.

● Strong communication and leadership skills, with experience mentoring and guiding

junior team members.

● Self-starter attitude with a bias for action and ability to thrive in fast-paced environments.

● Master’s degree in Machine Learning, Artificial Intelligence, Statistics, or a related

field is preferred.

Preferred Qualifications:

● Experience deploying ML systems in microservices or event-driven architectures.

● Hands-on experience with vector databases, embeddings, and retrieval-augmented

generation (RAG) systems.

● Understanding of Responsible AI principles and practices.

Why Join Us?

● Lead the ML charter in a mission-driven company solving real-world challenges.

● Work on cutting-edge LLM use cases and platformize ML capabilities for scale.

● Collaborate with a passionate and technically strong team in a high-impact environment.

● Competitive compensation, flexible working model, and ample growth opportunities.