Machine Learning Engineer

**Job Information**:
Industry
- IT Services

Date Opened
- 04/25/2025

Job Type
- Temporary

Remote Job

This is a remote position.

**About Slash**:
Slash is a hi-tech startup studio with a mission to build tech products that change the world. Our clients are global. In addition, we build and invest our own startups and commercialize them through joint ventures in ASEAN and Europe. We work on a wide-range of technologies: web, mobile, AI, blockchain, cloud, microservices & middlewares, security & infrastructure, etc.

Slash has headquarters in Singapore and community-oriented R&D hubs in Phnom Penh, Bali, Yogyakarta, Jakarta and Bandung. We are a team of 50+ entrepreneurs, engineers, hackers, and full-stack developers with unique capabilities in web, mobile, AI, and Blockchain.

**Role and responsibilities, and how will the role impact Slash?**:
About the role
We are seeking a highly motivated and experienced Machine Learning/Data Science Contractor to join our team in developing cutting-edge solutions for a critical maritime-related project. As a key member of our development team, you will play a crucial role in designing, building, and implementing machine learning models to predict and analyze patterns from various data sources. You will be working extensively with spatiotemporal data, developing solutions that integrate geospatial and temporal patterns to deliver actionable insights. This is a challenging and impactful project with the potential to significantly improve risk management in a key sector. This role requires a strong background in machine learning and significant experience with the Google Cloud Platform (GCP). If you're passionate about building cutting-edge solutions and working in a dynamic environment, we’d love to hear from you

**Key Responsibilities**:

- Model Development & Implementation: Develop, and implement machine learning models to predict and classify based on various data sources, including activity data, historical records, and environmental data.
- Data Exploration & Preprocessing: Perform exploratory data analysis (EDA) to understand the characteristics of data, identify patterns, and prepare data for model training.
- Feature Engineering: Create and select relevant features from raw data to improve model performance and interpretability.
- Model Selection & Evaluation: Experiment with different machine learning algorithms (supervised, semi-supervised, and unsupervised) and evaluate their performance using appropriate metrics.
- Algorithm Implementation: Develop and implement algorithms using modern tools, and coding practices, to ensure scalability and maintainability.
- Deployment: Containerize the algorithm for deployment on a cloud based system (GCP).
- Model Tuning & Optimization: Fine-tune model parameters to achieve optimal performance and address issues such as overfitting and bias.
- Collaboration: Collaborate with data engineers to process and analyze large datasets, leveraging GCP services such as BigQuery, Dataflow, and Dataproc.
- Staying Current: Stay up-to-date with the latest advancements in machine learning and deep learning techniques, particularly in the areas of sequence modeling, time series analysis, and anomaly detection.

**How do you know if you are a good fit?**:

- 5+ years of experience in developing and implementing machine learning models in a production environment.
- Strong understanding of machine learning, including deep learning, time series analysis, and anomalous pattern detection.
- Extensive experience with various machine learning techniques for classification, regression, clustering, and forecasting tasks (e.g., recurrent neural networks, ARIMA models, RCNNs).
- Proficiency in Python and relevant machine learning libraries (scikit-learn, TensorFlow, PyTorch).
- Experience with data manipulation and analysis libraries (e.g., Pandas, NumPy).
- Experience with data visualization tools (e.g., Matplotlib, Seaborn).
- Solid understanding of statistical concepts and techniques.
- Experience with feature engineering and model selection.
- Excellent communication and collaboration skills.
- Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP).
- Preferred Qualifications
- Experience working with the Google Cloud Platform (GCP) and its machine learning services (e.g., Vertex AI, AI Platform, BigQuery ML).
- Experience in developing and deploying models in a geospatial context is preferred.
- Experience with maritime data is a plus.

What do we offer?
- Projects/clients: Get the stability of a larger group and the excitement of a startup. Work on interesting global projects, challenges and technologies for top brands, fast-paced startups and governments. Experience working with a mature SCRUM team and day-to-day Agile mindset project implementation.
- Team and working environment: Join our diverse remote builders' community and hubs oriented in Indonesia, Cambodia, Singapore, and Thailand. Experience an optimized remote work