Data Scientist
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Job Location:
Monthly Salary:
Posted on:
30+ days ago
Vacancies:
1 Vacancy
Job Summary
Job Description:
Position Title: Data Scientist/Machine Learning Engineer
Experience: - Minimum 3 Years
Location: Remote
Employment Type: Full-Time with Rulesiq
Role Summary
We are seeking a highly skilled and versatile Data Scientist/Machine Learning Engineer to join our team. The ideal candidate will have a strong foundation in machine learning data science and software engineering coupled with the ability to design and implement end-to-end systems. This role involves working with cutting-edge technologies including LLMs recommendation models and NLP while leveraging big data engineering system design and cloud infrastructure to deliver impactful solutions.
Key Responsibilities
- Machine Learning & Data Science
- Develop and deploy machine learning models for various use cases such as recommendation systems propensity scoring and NLP.
- Design train and fine-tune large language models (LLMs) and integrate them into production workflows.
- Conduct exploratory data analysis (EDA) feature engineering and statistical modeling to derive actionable insights.
- Big Data Engineering
- Build and optimize data pipelines and workflows for large-scale data processing using tools like Apache Spark EMR or similar.
- Collaborate with the data engineering team to ensure data integrity scalability and efficiency.
- System Design & Development
- Architect and implement end-to-end ML systems from data ingestion to model deployment and monitoring.
- Develop robust and scalable APIs for model integration and data access.
- Ensure seamless integration with backend systems (MongoDB) and cloud infrastructure (AWS).
- Infrastructure & DevOps
- Containerize applications and ML models using Docker ensuring portability and consistency across environments.
- Orchestrate and manage deployments using Kubernetes.
- Monitor and optimize system performance ensuring high availability and reliability.
- Cloud Computing & Database Management
- Utilize AWS services such as S3 Lambda SageMaker and ECS for building and deploying solutions.
- Design efficient and scalable data storage solutions using MongoDB and related tools.
- Collaboration & Communication
- Work closely with cross-functional teams including data engineers software developers and product managers.
- Translate business requirements into technical solutions.
Requirements
Technical Skills
- Proficiency in Python with expertise in libraries such as NumPy Pandas Scikit-learn TensorFlow PyTorch and Hugging Face Transformers.
- Strong understanding of machine learning algorithms deep learning architectures and NLP techniques.
- Hands-on experience with recommendation systems propensity scoring and statistical methods.
- Knowledge of big data tools (e.g. Spark Hadoop) and stream processing.
- Solid experience with API development and integration.
- Expertise in Docker Kubernetes and CI/CD practices.
- Familiarity with AWS services and cloud-native architectures.
Analytical & Design Skills
- Strong grasp of data science concepts including predictive modeling clustering and classification.
- Experience with LLM fine-tuning and deployment for NLP applications.
- Sound understanding of system design principles and infrastructure best practices.
Education & Experience
- Bachelors or Masters degree in Computer Science Data Science or a related field.
- 3 (3-5)years of professional experience in machine learning engineering or data science roles.
- Previous experience in building and deploying end-to-end ML pipelines in production environments.
Nice-to-Have Skills
- Experience with MongoDB Atlas and serverless architectures.
- Knowledge of MLOps tools and practices for productionizing ML models.
- Familiarity with monitoring and observability tools (e.g. Prometheus Grafana).
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
