Machine Learning Engineer Id27476

What you will do
- Develop efficient, clean, and maintainable Python code for machine learning pipelines, leveraging our in-house libraries and tools;
- Collaborate with the team on code reviews to ensure high code quality and adhere to best practices established in our shared codebase;
- Contribute to building and maintaining our MLOps infrastructure from the ground up, with a focus on extensibility and reproducibility;
- Take ownership of projects by gathering requirements, creating technical design documentation, breaking down tasks, estimating efforts, and executing with key performance indicators (KPIs) in mind;
- Optimize machine learning models for performance and scalability;
- Integrate machine learning models into production systems using frameworks like SageMaker;
- Stay up-to-date with the latest advancements in machine learning and MLOps;
- Assist in improving our data management, model tracking, and experimentation solutions;
- Contribute to enhancing our code quality, repository structure, and model versioning;
- Help identify and implement the best practices for ML services deployment and monitoring;
- Collaborate on establishing CI/CD pipelines and promoting deployments across environments;
- Address technical debt items and refactor code as needed.

Must haves
- **3+ years** of experience in **machine learning engineering** or a related role;
- Strong proficiency in **Python** programming;
- Experience with machine learning frameworks such as **PyTorch, TensorFlow, or scikit-learn**;
- Familiarity with cloud platforms like **AWS**, including services like **SageMaker, S3, and Secrets Manager**;
- Experience with data processing, cleaning, and feature engineering for structured and unstructured data;
- Knowledge of software development best practices, including version control (Git), testing, and documentation;
- Excellent problem-solving and debugging skills;
- Strong communication and collaboration abilities;
- Ability to work independently and take ownership of projects;
- Upper-intermediate English level.

Nice to haves
- Experience with Infrastructure as Code (IaC) tools, preferably Pulumi or Terraform;
- Experience with classification models and libraries such as XGBoost, SentenceTransformers, or LLMs;
- Knowledge of data versioning, experiment tracking, and model registry concepts;
- Familiarity with data pipeline and ETL tools like Dagster, Snowflake, and DBT;
- Experience with monitoring logs, metrics, and performance testing for batch inference workloads;
- Contributions to open-source machine learning projects;
- Experience with deploying and monitoring machine learning models in production.

**The benefits of joining us**
- **Professional growth**:Accelerate your professional journey with mentorship, TechTalks, and personalized growth roadmaps.
- **Competitive compensation**:We match your ever-growing skills, talent, and contributions with competitive USD-based compensation and budgets for education, fitness, and team activities.
- **A selection of exciting projects**:Join projects with modern solutions development and top-tier clients that include Fortune 500 enterprises and leading product brands.
- **Flextime**:Tailor your schedule for an optimal work-life balance, by having the options of working from home and going to the office, whatever makes you the happiest and most productive.

AgileEngine is one of the Inc. 5000 fastest-growing companies in the US and a top-3 ranked dev shop according to Clutch. We create award-winning custom software solutions that help companies across 15+ industries change the lives of millions

If you like a challenging environment where you’re working with the best and are encouraged to learn and experiment every day, there’s no better place - guaranteed :)