Senior Data Scientist - Core Machine Learning

Who we are

Artmac Soft is a technology consulting and service-oriented IT company that provides innovative technology solutions and services to customers.

Job Description:

Job Title : Senior Data Scientist Core Machine Learning

Job Type : W2/C2C

Experience : 8-12 Years

Location : San Jose, California (On-Site)

Role Summary:

We are seeking a hands-on Senior Data Scientist to architect, develop, and productionize enterprise-scale machine learning solutions. This client-facing role requires deep expertise in feature engineering, ML architecture, end-to-end pipelines, model routing, and production observability, along with the ability to translate complex business requirements into scalable ML solutions.

Responsibilities:

Design and develop predictive, classification, recommendation, ranking, and deep learning models, selecting appropriate architectures based on business and technical requirements.
Lead feature engineering, exploratory data analysis, statistical validation, experimentation, and model performance optimization.
Own end-to-end ML pipelines, including data ingestion, training, deployment, monitoring, and automated retraining.
Design model routing and selection strategies, including embedding-based routing, confidence thresholds, fallback mechanisms, and output validation.
Implement production observability, drift detection, automated recovery, alerting, and model rollback strategies.
Collaborate directly with client stakeholders and cross-functional teams to define ML solutions, communicate architectural decisions, and drive production delivery.
Mentor junior data scientists and contribute to ML engineering best practices.

Required Experience & Skills :

8+ years of hands-on experience in applied machine learning and data science, with proven ownership of production ML solutions.
Strong expertise in feature engineering, ML algorithms, model architecture, statistics, experimentation, and A/B testing.
Advanced Python and SQL proficiency, with experience in scikit-learn and PyTorch or TensorFlow.
Experience with large-scale data processing using Spark/PySpark and cloud ML platforms such as AWS SageMaker, Azure ML, or Google Vertex AI.
Hands-on experience with MLOps, MLflow or equivalent, Docker, Kubernetes, CI/CD and model lifecycle management.
Experience implementing model routing, fallback logic, observability, drift monitoring, and automated recovery.
Strong communication skills and experience presenting technical solutions to client stakeholders.

Qualification:

• Bachelor's degree or equivalent combination of education and experience.