Data Scientist | Machine Learning Engineer | MLOps Engineer

Key Skills

Java Programming, Python Programming, C++, C Programming, SQL, Apache Hadoop, Scala Programming, Machine learning techniques, Data science techniques, PyTorch, TensorFlow, MapReduce, R Programming

Job Description

Job Description

Assembly Test and Technology Development (ATTD) Pathfinding Data Science team is newly formed and is tasked with developing AI models and analytics to make ATTD strategic initiatives. We are looking for experienced Machine Learning (ML) engineer to join our team to work on an Artificial Intelligence (AI) model productization. The successful candidate will engage in developing ground truth ML Operations (MLOps) infrastructure and integration of AI models on top.
Responsibilities will include:

• Building ML workflows and infrastructure at on-premise Intel Cloud to productize Proof of Concept (PoC) AI models and sustain them in production
• Developing automation of ML pipeline/warehouse at scale, cycle over cycle validation on feature importance and performance of ML models, and deploying AI applications as a continuous delivery in production

Qualifications

You must possess the below minimum qualifications to be initially considered for screening candidates. Preferred qualifications are in addition to the minimum requirements and are considered a plus factor in identifying top candidates.

Minimum Qualifications:

• Bachelor's Degree with 4+ years of relevant experience,
• Master's Degree with 3+ years of relevant experience,
• PhD with 1+ years of relevant experience in Computer Science, Data Science, or any relevant field
• Experience with SQL database(DB) management through DBaaS (Data Base as a Service)
• Experience in ML application development experience by Python and/or R which includes data pipeline creation, feature engineering, model selection and validation, application development and deployment
• Understanding of DevOps(Development Operations), MLOps(ML Operations), or container based application development(Docker, Kubernetes, etc.)
• Proven track record of deployment of production grade system

Preferred Qualifications:

• Prior knowledge and/or experience of:
• semiconductor manufacturing or relevant field
• Kubeflow
• Linux Virtualization
• AI application development by following web application frame (Rshiny, Streamlit, Plotly Dash, REST/FAST API, etc.)
• modern web application development frame, such as Kubernetes and Microservices
• NoSQL DB management, such as Neo4j Graph DB, connecting graph based data science analysis from/to tabular based data analytics environment such as in jupyter notebook