Senior Machine Learning Scientist Jobs

● Production experience utilizing Diffusion-based text-to-image generative models with Python as a base for image generation systems

● Production based experience developing image generative algorithms and large language models

● Production based experience architecting, developing, and deploying production Python applications

● Production experience working with MLOps pipelines

● Strong knowledge of deep learning, natural language processing, and generative AI

● Experience in data processing and analysis, statistical analysis, and data visualization

2-3 years of engineering experience 

Proficient knowledge of Python and SQL 

Experience with containers, Docker and Git 

Experience with cloud platforms (e.g. AWS, GCP, Azure, Databricks, etc) and associated machine learning products, e.g. Amazon SageMaker, Azure ML 

Experience in big data technologies, e.g. Hadoop, BigQuery, MapReduce, Apache Spark  

Experience working according to agile principles 

- Monitor and maintain deployed models, making necessary updates as data and business requirements change.

- Excellent problem-solving skills and the ability to translate business needs into technical solutions.

- Strong communication skills and the ability to work effectively in a team environment.

machine learning, data analysis, and programming

- Collect, clean, and preprocess data from various sources to create robust datasets for model development.

- Perform exploratory data analysis (EDA) to identify trends, patterns, and potential issues in the data.

Previous Machine Learning experience (5+ years)

Previous experience productionizing NLP models

Strong experience with Python, TensorFlow/ PyTorch

PhD qualification in computer science or equivalent

MS/ PhD in computer Science (related field)

Exposure to data pipeline frameworks (KubeFlow, AirFlow, MLFlow, etc.)

Experience in working with AWS cloud environment and large databases (e.g., AWS redshift).

Proficiency in SQL. Experience with PySpark is a plus.

Experience in managing ML lifecycle using open-source tools (e.g., MLflow).

Experience with developing web apps and real-time dashboards for data science and ML using open-source tools (e.g., Streamlit).

Solid understanding of omics data and hands-on experience with analyzing such datasets.

Design, train, and evaluate survival, classification, and regression ML models using appropriate algorithms and frameworks.

Build industry-leading recommendation system, improving user experience, content ecosystem and platform security;

Bachelor degree in computer science or a related major, with 3+ years of related work experience;

Strong software development experience with C++, Python or other programming language;

Strong communication and teamwork skills;

Deliver end-to-end machine learning solution to address critical product challenges;

Own the full stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.

5+ years of relevant work experience in Data Science organization, preferably in the CPG (Consumer Packaged Goods) industry.

Knowledge and application of scientific computing methods i.e., Python, R, Scala

Experience in one of more advanced analytic mythologies such as Machine Learning, Optimization, Simulation.

Experience with large data sets and cloud computing.

Experience with Dev Ops environment: Git, CICD, etc.

Would you enjoy solving billion-dollar data science problems across trillions of data points?

Master and above degree in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)

5+ years of related industry experience in the machine learning domain

Experience building and scaling machine learning models in business applications using large amounts of data

Experience building NLP related applications

Agile development mindset, appreciating the benefit of constant iteration and improvement

You will report to the Core Machine Learning Senior Manager.

Experience delivering impact in the domain of Content Recommendation, Text Classification, Knowledge Graphs.

Manage AI/ML projects to achieve the desired outcome promptly

Master or equivalent in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)

5+ years of related industry experience in the data science domain

Experience building and scaling machine learning models in business applications using large amounts of data

Agile development mindset, appreciating the benefit of constant iteration and improvement

Industry experience (based on the above requirement), preferably in a small start-up environment, working on early-stage drug discovery applications.

Knowledge of chemical informatics, molecular modeling, and drug discovery workflows.

Mentor, learn, and share cross-disciplinary knowledge with others along the way.

Tax-advantaged commuter benefits for public transportation or parking.

Strong passion for using machine learning to improve our world.

A track record of developing novel machine-learning solutions for real-life problems.

Healthcare knowledge: Previous experience is beneficial but not required.

Communication and teamwork: Good communication skills to collaborate effectively with cross-functional teams. Willingness to collaborate and learn with team members.

Work primarily performed in a hybrid environment consisting of in-office and working from home.

One-time furniture and equipment allowance for employees working from home

one-time furniture and equipment allowance for employees working from home

Reducing our members’ claim costs using both supervised and unsupervised approaches.

Automate model monitoring, model retrain, model deployment process based on business requirement

Outstanding analytical and problem-solving skills; Ability to learn quickly and detail oriented

Experience with machine learning operations

Deep knowledge of math, probability, statistics and algorithms

Experience with data modeling for both OLAP and OLTP databases, hands-on experience with SQL, especially SparkSQL performance tuning

Experience with software DevOps CI/CD tools, such GitLab

1+ year of Google Cloud Platform (GCP) experience, including certifications

Strong oral, written and interpersonal communication skills

Legal or regulatory domain experience

5+ years of experience, including both full-time work and research/academia experience, in mathematical programming, data mining, statistical analysis, and/or machine learning

Experience in one or more of the following domains: NLP, forecasting algorithms, large scale optimization, and deep learning

The minimum requirements we seek:

Minimum 1 year of work experience - Remote (US/Canada residing people only, with work permit)

Collaborate with cross-functional teams to identify business requirements and translate them into technical solutions.

Experience with popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).

Excellent problem-solving and analytical skills.

Strong communication and teamwork abilities.

Special Benefits You Will Love

Minimum 1 year of work experience - Remote (US/Canada residing people only, with work permit)

Collaborate with cross-functional teams to identify business requirements and translate them into technical solutions.

Experience with popular machine learning libraries (e.g., TensorFlow, PyTorch, scikit-learn).

Excellent problem-solving and analytical skills.

Strong communication and teamwork abilities.

Special Benefits You Will Love

Required Qualifications, Capabilities, And Skills

Preferred Qualifications, Capabilities, And Skills

Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community

Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)

Knowledge in search/ranking, Reinforcement Learning or Meta Learning

Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments

Required Qualifications, Capabilities, And Skills

Preferred Qualifications, Capabilities, And Skills

Research and explore new machine learning methods through independent study, attending industry-leading conferences, experimentation and participating in our knowledge sharing community

Extensive experience with machine learning and deep learning toolkits (e.g.: TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas)

Knowledge in search/ranking, Reinforcement Learning or Meta Learning

Scientific thinking with the ability to invent and to work both independently and in highly collaborative team environments

3 ~ 6 years of experience in a data science or machine learning role, ideally within finance or private equity setting

Strong programming skills and hands-on experience with Python (Numpy, SCipy, Pandas, Sscikit-learn, etc..)

Experience in implementing and managing ML models in production, including validation, scaling, and monitoring

Strong problem-solving skills, data and statistical analysis skills

Excellent verbal and written communication skills

Experience with MLOps tools and practices (preferred)

Good Machine Learning foundations, practical experience with classification, regression and clustering methods

Exposure/experience in NLP is preferable, experience with Deep Learning methods is preferable

Strong python coding, computing fundamentals/data structures, SQL, experience with Hadoop stack

Experience leading end-to-end data science project implementation

Experience in the healthcare sector preferred

Strong Machine Learning foundations, practical experience with classification, regression and clustering methods

Effective communication skills to convey technical concepts to both technical and non-technical audiences.

Experience with active learning, reinforcement learning, causal inference, and/or online learning approaches.

Knowledge of experimental design and Bayesian uncertainty estimation.

A deep passion for AI and a strong interest in building machine learning systems.

Proficiency in working with data using Python and SQL.

Familiarity with the entire ML stack, from initial research and development to model deployment in production environments.