Computer Vision Engineer - Machine Learning/Open Source

ROLE AND RESPONSIBILITIES

Should be able to work as an individual contributor and maintain good relationship with stakeholders. Should

be proactive to learn new skills per business requirement. Familiar with extraction of relevant data, cleanse and

transform data into insights that drive business value, through use of data analytics, data visualization and data

modeling techniques.

QUALIFICATIONS AND EDUCATION REQUIREMENTS

Technical Bachelor’s Degree.

Non-Technical Degree holders should have 1+ years of relevant experience.

  Strong knowledge in statistical and data mining techniques: GLM/Regression, Random Forest, Boosting, Trees, text mining, etc. 

 Sound Knowlegde querying databases and using statistical computer languages: R, Python, SQL, etc. 

 Strong understanding creating and using advanced machine learning algorithms and statistics: regression, simulation, scenario analysis, modeling, clustering, decision trees, neural networks, etc. 

Job Responsibilities:-

• Develop robust, scalable and maintainable machine learning models to answer business problems against large data sets.
• Build methods for document clustering, topic modeling, text classification, named entity recognition, sentiment analysis, and POS tagging.
• Perform elements of data cleaning, feature selection and feature engineering and organize experiments in conjunction with best practices.
• Benchmark, apply, and test algorithms against success metrics. Interpret the results in terms of relating those metrics to the business process.
• Work with development teams to ensure models can be implemented as part of a delivered solution replicable across many clients.
• Knowledge of Machine Learning, NLP, Document Classification, Topic Modeling and Information Extraction with a proven track record of applying them to real problems.
• Experience working with big data systems and big data concepts.
• Ability to provide clear and concise communication both with other technical teams and non-technical domain specialists.
• Strong team player; ability to provide both a strong individual contribution but also work as a team and contribute to wider goals is a must in this dynamic environment.
• Experience with noisy and/or unstructured textual data.

knowledge graph and NLP including summarization, topic modelling etc

• Strong coding ability with statistical analysis tools in Python or R, and general software development skills (source code management, debugging, testing, deployment, etc.)
• Working knowledge of various text mining algorithms and their use-cases such as keyword extraction, PLSA, LDA, HMM, CRF, deep learning & recurrent ANN, word2vec/doc2vec, Bayesian modeling.
• Strong understanding of text pre-processing and normalization techniques, such as tokenization,
• POS tagging and parsing and how they work at a low level.
• Excellent problem solving skills.
• Strong verbal and written communication skills
• Masters or higher in data mining or machine learning; or equivalent practical analytics / modelling experience
• Practical experience in using NLP related techniques and algorithms
• Experience in open source coding and communities desirable.

Able to containerize Models and associated modules and work in a Microservices environment

• Research and develop statistical learning models for data analysis
• Collaborate with product management and engineering departments to understand company needs and devise possible solutions
• Keep up-to-date with latest technology trends
• Communicate results and ideas to key decision makers
• Implement new statistical or other mathematical methodologies as needed for specific models or analysis
• Optimize joint development efforts through appropriate database use and project design

Qualifications/Requirements:

• Masters or PhD in Computer Science, Electrical Engineering, Statistics, Applied Math or equivalent fields with strong mathematical background
• Excellent understanding of machine learning techniques and algorithms, including clustering, anomaly detection, optimization, neural network etc
• 3+ years experiences building data science-driven solutions including data collection, feature selection, model training, post-deployment validation
• Strong hands-on coding skills (preferably in Python) processing large-scale data set and developing machine learning models
• Familiar with one or more machine learning or statistical modeling tools such as Numpy, ScikitLearn, MLlib, Tensorflow
• Good team worker with excellent communication skills written, verbal and presentation

Desired Experience:

• Experience with AWS, S3, Flink, Spark, Kafka, Elastic Search
• Knowledge and experience with NLP technology
• Previous work in a start-up environment

Job Description

Want to make every line of code count? Tired of being a small cog in a big machine? Like a fast-paced environment where stuff get DONE? Wanna grow with a fast-growing company (both career and compensation)? Like to wear different hats? Join ThinkDeeply in our mission to create and apply Enterprise-Grade AI for all types of applications.

Seeking an M.L. Engineer with high aptitude toward development. Will also consider coders with high aptitude in M.L. Years of experience is important but we are also looking for interest and aptitude. As part of the early engineering team, you will have a chance to make a measurable impact in future of Thinkdeeply as well as having a significant amount of responsibility.

Experience

10+ Years

Location

Bozeman/Hyderabad

Skills

Required Skills:

Bachelors/Masters or Phd in Computer Science or related industry experience

3+ years of Industry Experience in Deep Learning Frameworks in PyTorch or TensorFlow

7+ Years of industry experience in scripting languages such as Python, R.

7+ years in software development doing at least some level of Researching / POCs, Prototyping, Productizing, Process improvement, Large-data processing / performance computing

Familiar with non-neural network methods such as Bayesian, SVM, Adaboost, Random Forests etc

Some experience in setting up large scale training data pipelines.

Some experience in using Cloud services such as AWS, GCP, Azure

Desired Skills:

Experience in building deep learning models for Computer Vision and Natural Language Processing domains

Experience in productionizing/serving machine learning in industry setting

Understand the principles of developing cloud native applications

Responsibilities

Collect, Organize and Process data pipelines for developing ML models

Research and develop novel prototypes for customers

Train, implement and evaluate shippable machine learning models

Deploy and iterate improvements of ML Models through feedback