Address
Form of workLANGUAGE
English.
WORK TYPE
Remote.
AVAILABILITY
Full-time schedule.
ABOUT US
Truckers move America's economy. At SmartHop, we're committed to leveling the playing field in the trucking industry for small fleet companies. Uplifting truckers is what moves us, and in doing so, we will change the industry.
Our tech-enabled platform provides easy load booking, data-driven strategy and decision-making, trucking management, and business solutions aimed at helping small fleets earn more and stress less.
We're proud to have been recognized by Forbes, in its list of America's Best Startup Employers 2023, and Built In, as one of the Best Places to Work in Miami for 2023, for our culture. We celebrate talented individuals who can bring new perspectives and new ways of thinking by fostering an environment of employee empowerment, inclusion, diversity, and authenticity whereby each team member is contributing to keep us ahead of the curve.
Founded in 2018, we are a global remote company with our headquarters in Miami. We are backed by investors such as Union Square Ventures, Sozo Ventures, Equal Ventures, and Las Olas VC. We raised $30 million in our series B funding at the start of 2022, bringing the company's total funding to over $46 million.
LOCATION
LATAM
About the Role
As a Senior Machine Learning & Data Engineer, you will be passionate, talented, and innovative with a strong cloud and data engineering background to design, build, and maintain robust data pipelines that feed our machine learning models, as we continue to scale our business and make a true impact in the trucking industry.
As part of our Machine Learning team, you will work alongside recognized experts to develop robust data pipelines and ML services.
Qualifications: Must Have
- 6+ years of experience in the field to be able to hit the ground running.
- 4+ years of experience with Python, with machine learning and data analysis frameworks such as Pandas.
- 2+ years experience supporting machine learning and analytics workloads.
- 4+ years of experience with SQL.
- Strong experience with data warehousing, ETL processes, and data pipeline development.
Technical Requirements
- Python, Pandas.
- SQL.
- Google Cloud Platform and tools such as Cloud Run.
- Apache Airflow.
- Snowflake, BigQuery or other data warehouses.
- BitBucket and other CI/CD tools.
- Flask, FastAPI, or other API development tools.
- Terraform.
- Scrum methodology.
- English (B2+).
- Plus: Google Cloud Dataflow.
- Plus: MLOps experience.
- Plus: Bash skills
- Plus: Kafka.
Key Responsibilities
- Develop and maintain data pipelines to feed machine learning models with high-quality data.
- Data extraction and management (API integrations).
- Orchestrate data science processes and improve our MLOps tools.
- Ensure data quality and availability throughout our data science ecosystem.
- Deliver software components and requirements on time.
- Consider non-functional requirements such as security, border cases, and scalability.
- Maintain test and debug code practices.
- Maintain source control process.
- Deploy in development and production environment.
- Analyze systems performance, security, and stability.
- Work with cross-functional teams to understand business requirements and design end-to-end solutions.
BENEFITS
- Computer.
- Unlimited paid time off or vacation time.
- Paid sick leave.
- Paid local holidays.
- Paid parental leave.
- Paid bereavement leave.
- Learning and development opportunities.
- Flexible remote work.
- Employee engagement activities.
- Office refresh stipend.
- And more...
BENEFITS
- Computer.
- Unlimited vacation.
- Paid sick leave.
- Paid local holidays.
- Paid parental leave.
- Paid bereavement leave.
- Learning and development opportunities.
- Flexible remote work.
- Employee engagement activities.
- Office refresh stipend.
- Health insurance, for US & COL.
- 401(k), for US.
- And more...
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