The worlds largest content recommendation platform, is hiring a Senior Machine Learning Engineer.
What are some of the things you do on a day-to-day basis?
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more
Our tech stack:
Python, Java, TensorFlow, Spark, Kafka, Cassandra, HDFS, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker.

The worlds largest content recommendation platform, is hiring a Staff Machine Learning Engineer.
What are some of the things you do on a day-to-day basis?
Be responsible for the entire algorithmic lifecycle in the company: data analytics, prototyping of new ideas, implementing algorithms models in a production environment and then monitoring and maintaining them
Turn algorithm prototypes into shippable products that will have a significant and immediate impact on the companys revenue
Work on a daily basis with some of the hottest trends in todays job market: machine/deep learning, big data analytics/engineering and cloud computing
Apply your scientific knowledge and creativity to analyze large volumes of diverse data and develop algorithmic solutions and models to solve complex problems
Influence directly on the way billions of people discover the internet
Work on projects such as Internet Personalization, Content Feed, Real Time Bidding, Video Recommendations and much more
Our tech stack:
Python, Java, TensorFlow, Spark, Kafka, Cassandra, HDFS, ElasticSearch, AirFlow, BigQuery, Google Cloud Platform, Kubernetes and Docker.

We are looking for a Machine Learning Engineer to join our Data Science group.
We are a fast-growing company that is building a multi-product platform for eCommerce brands, and the Data Science group is at the heart of our innovative solutions.
Our group works on fundamental challenges within the eCommerce space which span a variety of domains, such as Machine Learning, Deep Learning, NLP, Generative AI, Reinforcement Learning, Recommendation Systems, Computer Vision and more.
You will:
Build data pipelines & large scale solutions based on ML models.
Work with big data technologies (e.g., AWS, spark, airflow, k8s), ML technologies (e.g., pytorch, keras, mlflow) and software engineering technologies (e.g., git, docker, jenkins).
Collaborate with highly experienced developers and researchers.
Constantly learn new stuff.

A day in the life:
Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
Analyze our risk product, identify improvements, and communicate results with internal stakeholders, including leadership, to ensure these are incorporated into business processes.
Lead our risk model data science performance monitoring. Define, understand, and test opportunities to improve the product, and drive roadmaps through your insights and recommendations.
Deliver directions for future data science research that are related to the model performance.
Design data collection strategies and their applications for building new products. Collaborate with the data engineering team to define and implement data processing workflows.
Participate in the design of data preparation processes, ensuring seamless integration of business requirements and technical feasibility.
Exemplify and foster our humble, collaborative and impact-obsessed culture.

We're seeking a dynamic AI Guild Manager to spearhead our AI-first transformation.
This leader will build, manage, and inspire a cross-functional AI Guild focused on educating, ideating, and delivering cutting-edge AI solutions across our company. You'll work closely with the CEO and other stakeholders to embed AI concepts into our processes, product development, and decision-making. If you are passionate about driving innovation with AI, GenAI, ML, and NLP, and possess hands-on technical expertise with a strong entrepreneurial spirit, this is the perfect role for you!
What am I going to do?
Build and Lead the AI Guild: Recruit, retain, and provide guidance to a high-performing team of AI practitioners across various areas of expertise.
AI Strategic Vision: Partner with the CEO and executive team to establish and execute a company-wide AI strategy that aligns with business objectives.
Educate and Innovate: Design and run AI training programs for employees, and facilitate knowledge-sharing on best practices and potential applications of AI. Create a culture of continuous AI learning and exploration.
Ideation and Solutioning: Actively collaborate with various teams to understand problems and opportunities; ideate and prototype AI solutions.
Technical Acumen: Provide hands-on expertise in the design, development, and deployment of AI models, particularly using cutting-edge techniques in GenAI, ML, and NLP.

Our Research team is growing, and we are looking for a Senior ML Engineer to join the team.
Not Your Typical Senior ML Engineer Role
As an ML Engineer, you will play a key role in the challenge of developing our core product using cutting-edge technology and significantly contributing to our data-for-justice revolution. You possess extensive expertise in ML along with a solid foundation in models and infrastructure development.
There is no one way of doing things. We are open to new ideas and we encourage creativity, new initiatives and entrepreneurial minds.
Responsibilities:
Apply cutting-edge solutions while leveraging our in-house legal textual database, coupled with rich metadata of various features
Develop scalable models and tools using machine learning to extract information from unstructured text
Analyze and generate insights from legal documents using ML and GEN AI
Develop MLOps infrastructure to support our ML models and pipelines.
Work alongside machine learning experts, technologists, product managers, and legal domain experts from across the organization to solve complex problems.

Lead the data science field within the company.

Build & Refine the company's AI / ML algorithms.

Proactively seek new directions for tackling hard-to-crack problems, including devising real-world experiments and data collection.
Develop and implement advanced algorithms and models to process unstructured documents like PDFs, extracting insights through entity recognition.

Collaborate cross-functionally to translate business needs into actionable data science solutions, conducting thorough data analysis and feature engineering to uncover trends within unstructured data.

Working closely with the company's CTO and architect.

We are looking for exceptional hands-on data science, machine learning, and algorithms researchers. Our data science group builds well-crafted machine learning systems which are at the core of unique position to prevent online fraud. you will have the opportunity to analyze complex non-stationary data, innovate, acquire, and demonstrate a wide range of skills and expertise in machine learning while maintaining a focus on delivering systems to production and making an impact. If you possess strong analytical ability and the know-how to translate your ideas into reality, we would like to have the chance to talk to you.

What you'll be doing:
Research and develop innovative machine learning projects up to deployment in production.
Lead projects, initiatives, and multidisciplinary task forces in a dynamic business environment.
Mentor other data scientists, influence your teammates' projects, advise colleagues from other disciplines.
Solve complex, unique data science problems that do not have an off-the-shelf solution. Dive deep into complex and multi-dimensional data sets to identify patterns, anomalies, and potential fraud indicators.
Work closely with domain experts and researchers to integrate domain-specific knowledge into our fraud detection models. Collaborate on research projects to explore new approaches and technologies.
Employ a wide range of techniques from data science, machine learning, statistics, probability, algorithms, and whatever is necessary to solve the most crucial problems is facing.

we are looking for a Senior Data Scientist
Responsibilities

Working on projects across multiple DS disciplines (Tabular datasets, Vision, NLP, Bayesian modeling, etc..)
Apply complex analytical techniques to derive actionable insights.
Converting business needs into working data science projects (Identifying problems and providing solutions from ideation to deployment).
Conducting research and implementing new initiatives.
Working closely with our product, analysis, data and development departments.
Designing and Creating machine learning and DS pipelines used to ease, enhance and automate analysis tasks.
Optimizing and improving existing ML/DL models and pipelines.
Working with big data (BigQuery, SQL).

We are looking for exceptional hands-on data science, machine learning and algorithms researchers. Our data science group builds well-crafted machine learning systems which are at the core of unique position to prevent online fraud. you will have the opportunity to analyze complex non-stationary data, innovate, acquire and demonstrate a wide range of skill and expertise in machine learning, while maintaining a focus on delivering systems to production and making an impact. If you possess strong analytical ability and the know-how to translate your ideas into reality, we would like to have the chance to talk to you.

What you'll be doing:

Research and develop innovative machine learning projects up to deployment in production.
Solve complex, unique data science problems that do not have an off-the-shelf solution. Dive deep into complex and multi-dimensional data sets to identify patterns, anomalies, and potential fraud indicators.
Stay ahead of the curve by understanding the latest adversarial techniques fraudsters use.
Work closely with domain experts and researchers to integrate domain-specific knowledge into our fraud detection models. Collaborate on research projects to explore new approaches and technologies.
Employ a wide range of techniques from data science, machine learning, statistics, probability, algorithms, and whatever is necessary to solve the most crucial problems is facing.