Machine Learning Engineer

hace 2 semanas

Lima, Perú Blue Orange Digital A tiempo completo

**Company Overview**:
**Position Overview**:
At Blue Orange, you'll have the opportunity to work on cutting-edge projects, leveraging modern machine-learning and AI techniques to deliver tangible business outcomes and drive innovation in our data-driven solutions.

**Responsibilities**:

- **Develop and Implement Machine Learning and AI Models**:

- Design, build, and deploy advanced machine learning models.
- Improve model performance by conducting feature engineering, hyperparameter search, and metric selection.
- _ Optional: Experience working with classical NLP: Intent recognition, Named Entity Recognition (NER), and Part of Speech Tagging (POS). Using Sklearn, Spacy, and Hugging Face._
- Build LLM-based products and stay up to date with current developments. Proficiency using Hugging Face, OpenAI, Anthropic, and/or Cohere tools.
- Design and build custom APIs with tools like FastAPI.
- Build LLM orchestration systems with tools like LangChain, LLamaIndex, Semantic Kernel, and/or HayStack.
- Build predictive analytics and modeling products using tools like Sklearn, Sktime, XGboosts, and/or LightGBM.
- ** Data Analytics and Processing**:

- Analyze large, complex datasets to extract actionable insights and inform model development.
- Implement data preprocessing, cleansing, and quality checks to ensure data quality.
- ** Cloud-Native Solutions and MLOps**:

- Develop and maintain cloud-native machine learning solutions using any of the major clouds: AWS (Lambda, EMR, GLUE, ECS, EKS), GCP (GKE, Anthos, Cloud Run), and/or Azure (CA, KS).
- Implement and manage MLOps practices to automate and streamline the ML model deployment process. Using tools such as MLflow and/or Weights and Biases for storing metrics, artifacts, and experiments.
- ** Containerization Technologies**:

- Utilize containerization technologies like Docker and Docker-compose to ensure consistent and scalable deployment of machine learning models. Using FastAPI microservices.
- ** Quality Assurance and Best Practices**:

- Ensure the highest quality of machine learning models through rigorous testing and validation. Using unit and integration testing with CI/CD pipelines through GitHub actions.
- Advocate and adhere to best software (i.e., SOLID, DRY, Git version control, etc.) and machine learning (train, val, test data splits, baseline definition, overfitting management, etc) within the team.

**Requirements**:

- 1 - 3 years experience practicing ML/AI data engineering.
- Degree in Computer Science, Engineering, Mathematics, or a related field.
- Strong mathematical skills, particularly in statistics and linear algebra.
- Experience with NLP and LLM-based technologies and frameworks.
- Proficiency in programming languages such as Python,
- Experience with cloud-based technologies AWS, GCP, and/or Azure.
- Expertise in training and deploying ML/AI-powered solutions in cloud environments.

**Preferred qualifications**:

- Advanced degree in a relevant field.
- Publications in relevant AI/ML communities and journals.
- Deep Learning Expertise in Tensorflow and/or Pytorch
- Experience Fine-tuning OpenSource LLMs and deploying them.
- Great Expectations and/or DBT is a plus.

**Benefits**:

- Fully remote
- Flexible Schedule
- Unlimited Paid Time Off (PTO)
- Paid parental/bereavement leave
- Worldwide recognized clients to build skills for an excellent resume
- Top-notch team to learn and grow with

**Salary**: $54000 - $60000, USD (per year)

Blue Orange Digital is an equal-opportunity employer.

Background checks may be required for certain positions/projects.

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