Machine Learning Engineer 4
1 week ago
Job Summary
As part of Privacy and Data Protection Team the Machine Learning Engineer will be responsible for researching, building, and designing ML systems to build and automate predictive models at enterprise level. Candidate should have the ability to rapidly grasp new technologies and abstractions and apply them in a meaningful way.Job Description
Core Responsibilities
- Research, design, and implement ML algorithms and tools.
- Review and select appropriate data sets in a data warehouse.
- Select appropriate data representation and visualization methods.
- Identify and understand data distributions that affects model performance.
- Verify data quality with a small/large number of data samples.
- Transform and convert ML prototypes and models, e.g. change from SVM to Random Forest.
- Test and evaluate machine learning models and using results to improve them.
- Train and retrain systems when needed. Knowledge in active learning is a plus.
- Extending machine learning libraries if needed.
- Persist ML models for production environments.
- Identify technology issues, design resolutions, and proactive communication.
- Experienced in interpreting project requirements and technical specifications.
Employees at all levels are expected to:
- Degree in computer science, math, statistics, or a related degree.
- 5 years of relevant experience with building ML models and data pipelines.
- Experience in supervised and un-supervised ML models.
- Proficient in persisting ML models and deployment in production environment (operationalizing ML models).
- Data science certificates in machine learning, neural networks, deep learning, or related fields.
- Strong analytical, problem-solving and teamwork skills.
- At least 2 years of experience in any data engineering python frameworks like Pandas/Pyspark.
- Software engineering skills and strong experience in data science coding and programming languages, including Python, SQL, NoSQL
- Strong knowledge and experience working with Python-based ML libraries and packages such as NumPy, SciPy, Pandas, etc.
- Extensive experience in working with ML frameworks, e.g. scikit-learn and Keras.
- Experience working with data visualization, e.g. Matplotlib.
- Understand data structures, data modeling and software architecture.
- Experience with version control frameworks, GIT preferred.
- At least 1 year of experience in LLM, NER and NLP based models
- Experience with text extraction using OCR, data parsing and storage
Additional Skills:
- Extensive experience in working with advanced ML frameworks, e.g. TensorFlow, PyTorch, Spark ML, and Torch.
- Experience working deploying model with MLFlow.
- Experience working with Databricks/ AWS ML
- Experience is additional visualization tools, e.g. , Seaborn, Plotly, pydot, Dash, etc.
Disclaimer:
- This information has been designed to indicate the general nature and level of work performed by employees in this role. It is not designed to contain or be interpreted as a comprehensive inventory of all duties, responsibilities and qualifications.
We believe that benefits should connect you to the support you need when it matters most, and should help you care for those who matter most. That's why we provide an array of options, expert guidance and always-on tools that are personalized to meet the needs of your reality—to help support you physically, financially and emotionally through the big milestones and in your everyday life.
Please visit the benefits summary on our careers site for more details.
Education
Bachelor's DegreeWhile possessing the stated degree is preferred, Comcast also may consider applicants who hold some combination of coursework and experience, or who have extensive related professional experience.Certifications (if applicable)
Relevant Work Experience
7-10 YearsComcast is an equal opportunity workplace. We will consider all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability, veteran status, genetic information, or any other basis protected by applicable law.-
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