Position: Machine Learning Engineer Contractor
Company: Develux
Experience required: 3y
English level: upper

**What are we doing?**
Develux is an IT consulting and software development company with products for the US market and outsourcing services worldwide. The company has been on the market since 2014 and has achieved perfect results in our four business units. We have 350+ goal-oriented, passionate specialists who are open to new challenges.

Now we're looking for a **Machine Learning Engineer** to join our team.

What we offer:
You can be on a project or work with us on a long-term basis (**as a contractor**)

**Technical Requirements:**
- fluent English
- Python
- Scala/Java – Data pipelines
- Apache Airflow
- TensorFlow
- Jupyter Notebooks
- Kubeflow
- NLP Libraries
- ML libraries: Pandas, Numpy

**Machine Learning**
- Natural Language Processing, Deep Learning, Computer Vision
- Python (AI/Data Science)
- Cloudbased, AI Services, Keras, Pytorch
- Entity extraction (NLP - Python)
- MLflow (MLOps), Kubeflow (MLOps)
- Document extraction (NLP - Python)
 
**Cloud Engineering - Google Cloud Platform**
- Machine Learning
- Vertex AI
- BigQuery
- Google Kubernetes Engine
- Cloud Build
- Cloud Storage

**Responsibilities:**
- Machine Learning & Data Engineering:
Algorithm Development: Develop, optimize, and deploy machine learning algorithms for tasks including but not limited to Natural Language Processing, Deep Learning, and Computer Vision.
- Data Preprocessing: Work on data pipelines using Apache Airflow to preprocess and clean data for machine learning algorithms.
- Model Validation: Conduct rigorous validation of machine learning models to ensure their generalizability and applicability to real-world data.
- MLOps: Utilize MLflow and Kubeflow for machine learning operations, including model versioning, deployment, and monitoring.
- Cloud & DevOps:
Cloud Engineering: Manage and optimize cloud resources on Google Cloud Platform, including but not limited to Vertex AI, BigQuery, Google Kubernetes Engine, Cloud Build, and Compute Engine.
- Scalability: Ensure the scalability and robustness of machine learning deployments using Google Kubernetes Engine.
- Automated Workflows: Create automated workflows for ML model training and inference using tools like Apache Airflow.
- Collaboration & Communication:
Teamwork: Collaborate with cross-functional teams, including data scientists, software engineers, and business analysts to meet project objectives.
- Client Interaction: Engage directly with clients in the banking and finance sectors to understand their specific requirements and to provide tailored solutions.
- Documentation: Create thorough documentation of models, algorithms, and data transformations for internal and external stakeholders.
- Knowledge Sharing: Conduct internal training sessions and workshops to disseminate knowledge about the latest machine learning and cloud engineering techniques.

**Hiring process:**
- Screening call with our recruiter
- Technical interview with Hiring Manager
- Interview with Head of outsource
- Proposal for cooperation with Develux

We believe that people with different perspectives and lived experiences drive the company to create unique solutions.