Pluntra is a forward-thinking software and technology solutions company focused on building innovative, user-centered products that make a real impact. We specialize in creating scalable, high-performance applications that help businesses grow, adapt, and lead in a rapidly changing digital landscape.

Our mission is simple: turn great ideas into exceptional software. We partner with startups and establish companies alike to design, develop, and deliver solutions that are intuitive, efficient, and built to last.

At Pluntra, we combine creativity, collaboration, and technical excellence to push boundaries and bring visions to life — transforming complex challenges into elegant, effective results.

Role Description

Pluntra is seeking an innovative and highly skilled Machine Learning Engineer to design, develop, and deploy intelligent systems that power data-driven products and experiences. The ideal candidate combines a deep understanding of ML algorithms with strong software engineering skills and a passion for building scalable, production-ready solutions.

Key Responsibilities

Design, build, and deploy machine learning models for diverse business and product use cases.
Collaborate with data scientists, product managers, and engineers to translate requirements into scalable ML solutions.
Develop robust data pipelines and feature engineering processes to support model training and inference.
Optimize model performance, reliability, and efficiency in production environments.
Monitor and maintain deployed models, implementing retraining strategies and version control.
Contribute to architectural decisions and enhance overall ML infrastructure and tooling.
Stay up to date with the latest ML techniques, frameworks, and best practices, bringing innovative ideas to the team.

Qualifications

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Applied Mathematics, or a related field.
3+ years of experience as a Machine Learning Engineer, Data Scientist, or similar role.
Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, scikit-learn, or XGBoost.
Strong understanding of ML algorithms, model evaluation, and feature engineering.
Experience building end-to-end ML systems, from data ingestion to model deployment.
Familiarity with MLOps practices, including CI/CD for ML, model versioning, monitoring, and automation.
Experience with cloud platforms (AWS, GCP, or Azure) and containerization tools like Docker or Kubernetes.

Preferred Skills

Experience with large language models (LLMs), vector databases, or generative AI frameworks.
Familiarity with streaming data, real-time inference, or edge deployments.
Strong software engineering practices, including testing, code reviews, and clean architecture.
Experience with big data tools (e.g., Spark, Databricks, Kafka) is a plus.

How to Apply

Apply via our external site: https://pluntra.online/apply