Machine Learning Engineer 7278-2815
at Foilcon
Toronto, ON, Canada -
Start Date | Expiry Date | Salary | Posted On | Experience | Skills | Telecommute | Sponsor Visa |
---|---|---|---|---|---|---|---|
Immediate | 28 Jun, 2024 | Not Specified | 29 Mar, 2024 | N/A | Data Cleaning,Sentiment Analysis,Natural Language Processing,Algorithms,Data Quality,Models,Scikit Learn,It,Statistics,Text Classification,Tokenization,Tuning,Training,Numpy,Pandas,Deep Learning,Nlp,Python | No | No |
Required Visa Status:
Citizen | GC |
US Citizen | Student Visa |
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OPT | H4 Spouse of H1B |
GC Green Card |
Employment Type:
Full Time | Part Time |
Permanent | Independent - 1099 |
Contract – W2 | C2H Independent |
C2H W2 | Contract – Corp 2 Corp |
Contract to Hire – Corp 2 Corp |
Description:
ALL REQUIREMENTS ARE ‘MUST HAVE’:
(15%) Deep Understanding of Machine Learning Concepts: Proficiency in fundamental machine learning concepts, algorithms, and techniques.
Expertise in Natural Language Processing (NLP): Knowledge of NLP techniques and models, especially BERT and other transformer-based models, for tasks like text classification, sentiment analysis, and language understanding.
(20%) Experience with Deep Learning Frameworks: Proficiency in deep learning libraries such as TensorFlow or PyTorch. Experience with implementing, training, and fine-tuning BERT models using these frameworks is crucial.
(30%)Data Preprocessing Skills: Ability to perform text preprocessing, tokenization, and understanding of word embeddings.
Programming Skills: Strong programming skills in Python, including experience with libraries like NumPy, Pandas, and Scikit-learn.
(20%) Model Optimization and Tuning: Skills in optimizing model performance through hyperparameter tuning and understanding of trade-offs between model complexity and performance.
(15%) Understanding of Transfer Learning: Knowledge of how to leverage pre-trained models like BERT for specific tasks and adapt them to custom datasets.
General Skills:
- Experience managing available resources such as hardware, data, and personnel so that deadlines are met
- Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability
- Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Experience verifying data quality, and/or ensuring it via data cleaning
- Experience supervising the data acquisition process if more data is needed
- Experience finding available datasets online that could be used for training
- Experience defining validation strategies
- Experience defining the preprocessing or feature engineering to be done on a given dataset
- Background in statistics and computer programming
- A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experienc
Responsibilities:
Responsibilities:
- Creates machine learning models and utilizes data to train models
- Focuses on analyzing data to find relations between the input and the desired output
- Understands business objectives and develops models that help achieve them, along with metrics to track their progress
- Designs and develops machine learning and deep learning systems
Runs machine learning tests and experimentsImplements appropriate machine learning algorithms
General Skills:
- Experience managing available resources such as hardware, data, and personnel so that deadlines are met
- Experience analyzing the machine learning algorithms that could be used to solve a given problem and ranking them by their success probability
- Experience exploring and visualizing data to gain an understanding of it, then identifying differences in data distribution that could affect performance when deploying the model in the real world
- Experience verifying data quality, and/or ensuring it via data cleaning
- Experience supervising the data acquisition process if more data is needed
- Experience finding available datasets online that could be used for training
- Experience defining validation strategies
- Experience defining the preprocessing or feature engineering to be done on a given dataset
- Background in statistics and computer programming
- A team player with a track record for meeting deadlines, managing competing priorities and client relationship management experience
Skills
Experience and Skill Set Requirements
REQUIREMENT SUMMARY
Min:N/AMax:5.0 year(s)
Information Technology/IT
IT Software - Other
Software Engineering
Graduate
Proficient
1
Toronto, ON, Canada