About the role
We are looking for a Senior Data Scientist to develop, deploy, and maintain production machine learning models in a cloud-native enterprise environment. You will build and improve data pipelines supporting ML workflows, perform exploratory data analysis and feature engineering, and collaborate with engineering and business stakeholders to deliver scalable ML solutions using AWS SageMaker or equivalent enterprise ML platforms. The role requires 4+ years of production ML experience with strong Python and advanced SQL skills, and includes contribution to AI and LLM-based capabilities where applicable.
What you will do
- Develop, deploy, and maintain production machine learning models.
- Perform exploratory data analysis and feature engineering.
- Build and improve data pipelines that support ML workflows.
- Collaborate with engineering and business stakeholders to deliver scalable ML solutions.
- Contribute to AI/LLM-based capabilities where applicable.
Must haves
- 4+ years of experience building and maintaining production machine learning models.
- Strong Python programming skills.
- Experience with AWS SageMaker or another enterprise ML platform, such as Vertex AI or Azure ML, supporting production ML pipelines.
- Experience deploying and monitoring ML models in production, not only notebook-based development.
- Advanced SQL skills.
- Git and version control experience.
- Experience working independently in production environments.
- Experience building scalable ML solutions in enterprise environments.
- Familiarity with cloud-based ML platforms and production deployment best practices.
- Strong communication skills and the ability to work with cross-functional teams.
Nice to haves
- Experience with MLOps tools such as MLflow, Airflow, dbt, or similar.
- Experience with Snowflake.
- Marketing, growth, experimentation, or causal inference experience.
- Experience with LLMs or AI agents.
- Familiarity with Agile development practices.
Perks
- Growth without limits: build your skills through mentorship, internal TechTalks, challenging projects, and a dedicated annual learning budget
- Competitive compensation: get recognition that reflects your skills and impact, with regular performance and compensation reviews
- Flexibility: work 100% remotely with flexible hours that support focus, autonomy, and a healthy work rhythm
- Meaningful, modern projects: build impactful products using modern technologies alongside global teams and leading brands
- Collaborative culture: join a supportive environment with zero micromanagement where ideas are welcomed and contributions are recognized
- Well-being & support: access local well-being programs and people-focused support tailored to your location
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Hiring process timeline
We designed our hiring process to be fast, transparent, and convenient — so you always know what to expect and can move through the steps without unnecessary delays.
A quick note
After applying, keep an eye on your inbox — including your spam folder. Occasionally, emails from our hiring platform, LaunchPod, may land there.
Tell us about yourself
Submit a short application form.
Pass a quick test
Pass a 30’- 60’ test.
Record a short video
Introduce yourself on video to fast-track your application process.
Meet our team
Once you pass the video review, grab a spot on our calendar for a technical interview.
Get an offer
Welcome to AgileEngine!
Have any questions?
What is the work format and schedule?
We are a remote-first company, so all our positions are remote. Schedules are flexible, but the main requirement is to have an overlap with your client’s schedule to ensure smooth collaboration. Specific details depend on the project and are discussed during the interview process.
What level of English is required?
We look for Upper-Intermediate (B2) proficiency or higher. Since you will be collaborating with international teams and global clients (including Fortune 500 companies), English is a part of your daily work.
Does AgileEngine provide work equipment?
It depends on your location. We provide equipment in Ukraine, Poland, Argentina, Colombia, Mexico, Brazil, Guatemala, Portugal, Spain, and India. In the USA, equipment is usually provided by the client; otherwise, you will be expected to use your own setup.
What opportunities for professional growth do you offer?
We support continuous growth through personalized development paths tailored to each expert. Also, you can expect:
- An annual learning and development budget
- Internal workshops, tech talks, and mentorship programs
- Opportunities to switch projects or grow into new roles over time
What does a typical team look like, and what tools do you use?
Teams vary by project, but you’ll usually work with a mix of experts across different fields, along with a delivery or project manager who supports collaboration and onboarding.
For day-to-day work, teams commonly use tools like Jira and Google Workspace, along with communication platforms such as Google Chat. Depending on the client, you may also work with Slack, Confluence, Notion, or similar tools.
Need help?
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