What are the responsibilities and job description for the Machine Learning Engineer, Mid Level position at Jobright.ai?
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Job Summary:
Point72 is a leading global alternative investment firm, and they are seeking a Machine Learning Engineer to join their Compliance Product Development team. The role involves building production-ready applications specializing in natural language processing solutions to support front office investment professionals.
Responsibilities:
• Contribute to projects across various ML disciplines, including Natural Language Processing (NLP), unstructured data analysis, predictive modeling, and classic machine learning.
• Work with sparse data and apply techniques to improve model accuracy and generalization.
• Utilize SpaCy, Hugging Face Transformers, PyTorch, TensorFlow, and other NLP frameworks for model development.
• Implement MLOps strategies, including model versioning, automated retraining, monitoring, and CI/CD pipelines for ML workflows.
• Conduct data evaluation, including data preprocessing, feature engineering, and model performance assessment.
• Collaborate cross-functionally with data engineers, software developers, and product teams to integrate models into production systems.
• Stay up to date with the latest advancements in NLP and machine learning, applying new techniques as needed.
Qualifications:
Required:
• 5 years of experience in machine learning and NLP.
• Experience working in a Linux environment.
• Strong proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, and Scikit-learn.
• Hands-on experience with SpaCy, Hugging Face, and Transformers for NLP applications.
• Expertise in working with sparse data and applying techniques such as data augmentation, weak supervision, and semi-supervised learning.
• Experience deploying and managing ML models in cloud-based environments (e.g. AWS SageMaker).
• Strong understanding of MLOps principles, including automated model retraining, performance monitoring, and infrastructure scaling.
• Experience with data evaluation techniques, model explainability, and error analysis.
• Solid grasp of NLP concepts, including tokenization, embeddings, attention mechanisms, and transformer-based architectures.
• Experience fine-tuning large-scale NLP models and LLMs.
• Familiarity with knowledge graphs and graph-based NLP techniques.
• Background in unsupervised learning or self-supervised learning for NLP.
• Commitment to the highest ethical standards
Company:
Point72 invests in multiple asset classes and strategies worldwide. Founded in 2012, headquartered in Stamford, Connecticut, USA, team size 1001-5000 employees, currently Late Stage. Point72 has a track record of offering H1B sponsorships.
