Machine Learning Engineer – Remote Job.
Remote, Peru
Bertoni Solutions
We are a technology consulting company specializing in digital transformation, IT staff augmentation, custom software development and quality assurance.Company Description
We are a multinational team of individuals who believe that, with the right knowledge and approach, technology is the answer to the challenges businesses face today. Since 2016, we have brought this knowledge and approach to our clients, helping them translate technology into their success.
With Swiss roots and our own development team in Lima and across the region, we offer the best of both cultures: the talent and passion of Latin American professionals combined with the organizational skills and Swiss mindset.
Job Description
We are looking for a Machine Learning Engineer to design and implement machine learning models that solve real-world business challenges. The ideal candidate will have strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, AWS, Azure ML, and Kubernetes, with experience in deploying ML solutions in production environments.
On the other hand, we're currently processing candidates for this position and assessing the market for our talent pool/pipeline, as the role is expected to open soon. By joining our talent pool, you will have the advantage of completing part of the selection process in advance, allowing us to reach out to you quickly when the position becomes available. Additionally, we will always prioritize you when considering new opportunities that align with your profile.
Key Responsibilities:
- Develop and optimize machine learning models to address business problems.
- Implement, test, and deploy ML algorithms using frameworks like TensorFlow, PyTorch, and Scikit-learn.
- Work closely with data scientists and engineers to transform research prototypes into scalable solutions.
- Optimize model performance, scalability, and efficiency for deployment in cloud and on-premise environments.
- Deploy and manage ML models using AWS, Azure ML, and Kubernetes.
- Monitor model performance, retrain as needed, and ensure reliability in production.
- Collaborate with cross-functional teams to integrate ML models into business applications.
Qualifications
IMPORTANT: This opportunity is exclusively available for bilingual applicants (Spanish or Portuguese native and English advanced fluency) currently located in Latin America. If you do not meet these criteria, we kindly ask that you refrain from applying, as applications that do not meet these requirements will not be considered.
Required:
- +5 years of experience with the role.
- Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with cloud platforms (AWS, Azure ML) for deploying ML solutions.
- Knowledge of Kubernetes for container orchestration and scaling ML workloads.
- Familiarity with data pipelines, feature engineering, and model evaluation techniques.
- Experience deploying and monitoring ML models in production environments.
- Strong problem-solving skills and ability to work in an agile environment.
- Advanced written and spoken English fluency is a must have.
Preferred Qualifications:
- Experience with MLOps practices and tools.
- Understanding of big data processing frameworks (Spark, Dask, etc.).
- Knowledge of CI/CD pipelines for ML model deployment.
- Familiarity with deep learning architectures and NLP techniques.
Additional Information
- Type of Contract: Independent Contractor/fee for services (This contract type does not include tax withholding, PTOs, or insurance. Compensation is based on the number of hours worked per month.)
- Location: Our clients are located in the US, but the position is 100% remote.
- Time Zone and Work Hours: Full-time, Monday to Friday (8 hours a day, 40 hours a week). Time zone: US time zones (PST, MST, CST, or EST).
- Monthly rate: we don’t have a range yet, so we’re open to negotiating.
- Equipment: The contractor will use their own laptop/PC.
Bertoni´s interview process
- Screen interview (cultural fit, english test, requirements verification)
- Background check
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: Agile Architecture AWS Azure Big Data CI/CD Data pipelines Deep Learning Engineering Feature engineering Kubernetes Machine Learning ML models MLOps Model deployment NLP Pipelines Python PyTorch Research Scikit-learn Spark TensorFlow
Perks/benefits: Career development Gear
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