Engineer, Machine Learning

**Job Summary**:
Build and improve machine learning and analytics platform. Work with data scientists to create, optimize and productionize of machine learning models for various business units within the organization. Keep innovating and optimizing data and machine learning workflow to enable data-driven business activities at large scale.

**Essential Duties and Responsibilities**:

- Participate and contribute to a team of 3-4 Data/Machine Learning/AI Engineers focused on high mix/low volume manufacturing
- Able to integrate data from Automation/Inspection/Packaging/Robotic machines and enable data collection from IoT devices on legacy machines and processes for Machine Learning and AI solutions
- Build and maintain data/solution pipelines that feed machine learning models
- Design and optimize data structures in data management systems (Hadoop, Snowflake, and Cloud platforms) to enable AI/ML solutions
- Build analytics platform components to support data collection, exploratory, and integration from various sources being data API, RDBMS, or big data platform.
- Create/Maintain CI/CD pipelines of machine learning solutions in the cloud
- Update job knowledge by studying state-of-the-art development tools, programming techniques, and computing equipment; participating in educational opportunities; reading professional publications; maintaining personal networks; and participating in professional organizations
- Protect operations by keeping information confidential
- Collaborate with other automation team members to define requirements, develop, and test solutions for ML and AI capable

**Knowledge, Skills and Abilities**:

- Experience and interest in working with: Python, C++, R.
- Statistical concepts like Mean, Standard Deviations, and Gaussian Distributions along with probability theory for algorithms like Naive Bayes, Gaussian Mixture Models, and Hidden Markov Models are necessary
- Competence in understanding Signal Processing and the ability to solve several problems using Signal Processing techniques is crucial
- Understanding of algorithms theories: Gradient Descent, Convex Optimization, Lagrange, Quadratic Programming, Partial Differential equation, and Summations
- Understanding of Neural network architectures to counter Translation, Image Processing and Speech Recognition
- Hands-on experience building ML, DL models using Sci-Kit Learn, TensorFlow, PyTorch
- Experience in CNN, RNN, NLP, BERT architectures.
- Exposure to open source MLOps tools like MLFlow, DVC
- Exposure to Amazon SageMaker, Google AutoML
- Hands-on experience in using Python libraries NumPy, Pandas, SciPy
- Hands-on experience in GitHub, GitLab for code versioning and deployment
- Exposure to SPC applied in manufacturing industry
- Fluent communications in explaining AI and ML concepts to different level and non-technical audience
- Exposure to MES, SAP and PLM system will be an advantage
- Must have the ability to work under deadline pressures and meet project objectives within a reasonable schedule
- Passion about machine learning and data-driven intelligence system
- Excellent communication and presentation skills in English
- Team player, self-starter, ability to work on multiple projects in parallel is necessary
- Strong work ethic. Fast learner with energy and enthusiasm
- Perform other duties as assigned

**Educational/Certification Requirement**:

- Masters/Bachelors in Computer Science, Computer Engineering, Statistics, Applied Mathematics, or related disciplines

**Experience Requirement**:

- 2 years+ in a role responsible for, or heavily involved in a data science team, developing Machine Learning and artificial intelligence strategy