Ml engineer

As a Machine Learning Engineer at Veronica Tech, you will be at the forefront of designing, developing, and deploying cutting‑edge AI solutions that power our next‑generation products. You will collaborate closely with data scientists, software engineers, and product managers to transform complex data sets into scalable models that deliver real‑world impact. The role offers a dynamic, fast‑paced environment where innovation is encouraged, and continuous learning is supported through access to state‑of‑the‑art tooling, mentorship programs, and cross‑functional workshops. You will be instrumental in shaping the architecture of our ML pipelines, ensuring robustness, performance, and ethical compliance while contributing to a culture of openness and shared ownership. This position provides the opportunity to see your work directly influence customer experiences and drive the company’s strategic growth.

Requirements: Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Mathematics, or a related field with 1–8 years of relevant experience. Proficiency in Python and experience with ML libraries such as TensorFlow, PyTorch, or Scikit‑learn. Strong understanding of data preprocessing, feature engineering, model evaluation, and deployment techniques. Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker and Kubernetes. Excellent problem‑solving abilities, effective communication skills, and a collaborative mindset.

Roles and Responsibilities: Design, implement, and optimize machine learning models for various business applications. Develop end‑to‑end ML pipelines, including data ingestion, preprocessing, training, validation, and deployment. Collaborate with data scientists to translate research prototypes into production‑ready solutions. Monitor model performance in production, troubleshoot issues, and iterate for continuous improvement. Ensure models meet security, privacy, and ethical standards throughout their lifecycle. Document code, processes, and best practices to promote knowledge sharing across the engineering team.

Budget: Job Type: Payroll Maximum Budget: $180,000 per year Experience Range: 1–8 years