Machine Learning Engineer
Worldwide | Oct. 22, 2026
Report as Closed
Company:
Improving
Country: Worldwide
Type: Remote
Employment: Full-time
Description: Improving is an IT services firm focused on AI, Data, and Applications. We modernize legacy systems, build cloud-native platforms, and deliver future-ready solutions through collaborative, long-term partnerships that drive measurable outcomes.
At Improving South America, we provide IT services to transform the perception of the IT professional. We focus on IT consulting, software development and agile training.
The company promotes an exceptional work culture based on teamwork, excellence and fun, with a focus on personal growth and shared rewards. By joining, the candidate will become part of a community that prioritizes open communication and strong long-term working relationships, supported by a structure of professional development and continuous learning.
- Strong production Python (3.12+), well beyond scripting-level.
- Snowflake: writing and optimizing SQL, with an understanding of schema, warehouse and role concepts. Key-pair (JWT) authentication experience is a plus.
- Docker: building and optimizing container images, including packaging ML artifacts and their dependencies.
- Kubernetes: deploying and operating workloads (pods, deployments, resource limits, networking basics), with hands-on experience building, scheduling and debugging CronJobs.
- AWS: working knowledge of core services (S3, IAM, boto3). EMR experience is a plus.
- Log- and metrics-based troubleshooting across scheduled jobs and services (Elastic, Datadog or equivalent).
- Testing discipline: pytest fluency and the ability to design meaningful edge-case tests.
- Git/GitHub workflow fluency: feature branching, pull requests, code review.
- Comfort working in a fast-moving agile team and communicating clearly in writing.
At Improving South America, we provide IT services to transform the perception of the IT professional. We focus on IT consulting, software development and agile training.
The company promotes an exceptional work culture based on teamwork, excellence and fun, with a focus on personal growth and shared rewards. By joining, the candidate will become part of a community that prioritizes open communication and strong long-term working relationships, supported by a structure of professional development and continuous learning.
We are looking for an ML Engineer to join our data science and machine learning engineering team. The candidate will be responsible for designing, developing, and deploying advanced machine learning models, with an emphasis on clustering models, time series analysis, and complex heuristics.
Conditions
- Long-term contract.
- 100% Remote.
- Vacation and PTOs
- Possibility of receiving 2 bonuses per year.
- 2 salary reviews per year.
- English classes.
- Apple equipment.
- Online course platform
- Budget for purchase of books.
- Budget for purchasing work materials
- much more..
Desirable skills
- Model-serving or ML platform experience: KServe, Seldon, BentoML, MLflow or similar.
- Familiarity with common model artifact formats (scikit-learn, PyTorch, ONNX) and their packaging conventions, even if you have not trained the models yourself.
- Helm chart authoring and Terraform (including Datadog monitors and dashboards as code).
- Experience with LLM or agent infrastructure: RAG pipelines, vector stores, agent orchestration, MCP integrations, LLM evaluation harnesses or guardrails. This is the main differentiator for the Copilot side of the team.
- Experience with API gateways and production hardening of AWS-hosted services (for example Kong, secrets management, monitoring).
- Artifact repository publishing (JFrog Artifactory) and Gradle familiarity.
- Claude Code or similar AI coding tools, and spec-driven development.
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