Machine Learning Engineer
5 days ago
Company Description
McLaren Strategic Solutions (MSS) is a technology services and digital transformation company under McLaren Strategic Ventures, headquartered in California. MSS offers digital transformation services including Advisory Services, Product & Platform Engineering, and Technology Services. They leverage leading platforms for services and are a global leader in platform-based services.
Responsibilities
• Develop predictive models using supervised and unsupervised machine learning/deep learning
• Build models for legal predictive analytics, natural language understanding, conversational AI,robotic accounting, forecasting and anomaly detection
• Provide expertise in data wrangling, exploratory data analysis and feature engineering with largedata sets
• Support the development of proofs of concept to demonstrate the application of AI/MLcapabilities in solving customer problems in collaboration with product and other developmentteams
• Collaborate effectively with other teams
• A self-starter who can align the technology solution with a business goal
Qualifications
• Undergraduate or Graduate degree (MS or PhD) in Computer Science, Engineering, Mathematicsor equivalent, specializing in machine learning or a related field
• 3+ years’ experience in supporting development of production-ready solutions leveraging AItechnologies: NLP, Deep Learning, Machine Learning
• Strong hands-on expertise in Python and open source libraries/frameworks/tools such asNumPy, SciPy, scikit-learn, pandas, matplotlib, spaCy, NLTK, jupyter, anaconda, transformers,etc.
• Experience with deep learning frameworks such as TensorFlow, Keras, PyTorch
• Experience in applying deep learning to NLP
• Computer vision modeling a plus
• Experience with designing, building, and optimizing data and model training pipelines
• Experience in SageMaker or Azure ML Studio a plus
• Experience with cloud-based platforms (AWS or Azure) for solution delivery
• Experience working with agile and Software Development Lifecycle tools (e.g. JIRA, Confluence,Git) and Test-Driven Development (TDD
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