Robusta Technology Group (RTG) is a key driver of digital transformation by providing a holistic tech ecosystem. RTG works with its local and international partners to help build digital customer experiences, establish remote engineering hubs and build ventures across multiple industries and domains. In this pursuit, RTG serves as a catalyst for impact and growth through events, spaces and content focused on creating impact and growth across the different interactions. 

Robusta is a tech agency working with a diverse client base across different sectors & industries on implementing digital transformation programs. Engagements are typically focused on digitization of existing operations & processes and/or activation of digital customer engagement channels. With a team of 100+ tech and market consultants, robusta maintains an impactful footprint across EMEA and engages with its clients through its two key operations hubs in Egypt and Germany. 

Responsibilities:

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We seek someone with a good blend of business consulting skills and a data analytics background to add to our team.

Responsibilities:

• Apply advanced Data Science and MLOps techniques to solve key business problems.
• Collaborate with client stakeholders to translate business needs into high-level analytical solution designs.
• Present insights and solutions to business leaders, demonstrating impact and value.
• Manage analytics projects and coordinate with global client and Tiger teams.
• Lead requirement discussions, and oversee planning, development, and documentation of DS/AI solutions.
• Build and maintain strong client relationships to support account growth.
• Partner with technical teams to select appropriate analytical methods and generate actionable insights.
• Communicate results to senior leadership and support the operationalization of analytics solutions.

Requirements

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

You will collaborate with cross-functional teams and business partners and will have the opportunity to drive current and future strategy by leveraging your analytical skills as you ensure business value and communicate the results.

Requirements

About Jobgether

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Machine Learning Engineer - AI in India.

As a Machine Learning Engineer focusing on NLP, you will be responsible for designing, developing, and deploying machine learning and deep learning models, with an emphasis on Natural Language Processing (NLP) solutions. You will lead the development of cutting-edge NLP projects, guiding the creation and deployment of models in production while ensuring the professional management of these models throughout their lifecycle. In addition to your technical contributions, you will provide mentorship to team members and help shape the team's growth.

Accountabilities:

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

One of our companies is currently looking for a Senior Data Scientist in United States.

As a Senior Data Scientist, you will play a pivotal role in shaping and enhancing AI-driven financial crime detection solutions. You will develop, deploy, and optimize machine learning models focused on anomaly detection to detect money laundering and fraudulent activities. In this hands-on role, you will collaborate with cross-functional teams, guide junior data scientists, and engage with customers to ensure that AI solutions are scalable, reliable, and meet market expectations. This is an exciting opportunity to contribute to impactful, cutting-edge technologies in the fight against financial crime.

Accountabilities:

AHOY is seeking a talented AI Engineer to join our innovative team dedicated to pushing the boundaries of artificial intelligence technology. In this role, you will develop and implement AI models and algorithms that enhance our products and services. You will be a critical player in designing solutions that optimize operations, improve user experience, and drive business results.

Key Responsibilities:

• Design and develop AI-based applications including machine learning models, natural language processing tools, and predictive analytics solutions.
• Implement algorithms and models to improve performance and scalability across various platforms.
• Collaborate with data analysts and software engineers to gather requirements and translate business needs into technical specifications.
• Analyze large datasets to derive actionable insights and enhance existing AI models.
• Conduct research on advanced AI algorithms and technologies, evaluating their applicability to current projects.
• Document processes, methodologies, and technical specifications to facilitate knowledge sharing within the team.
• Monitor model performance and iterate on design based on real-world feedback and data.

Requirements

Qualifications:

Tiger Analytics is looking for experienced Machine Learning Engineers to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world. You will be responsible for:

• ML Engineer with 5-7 years of IT experience.
• Pipeline Training Models, Building, Deployment, Testing, and Monitoring using AWS SageMaker, AWS CFT, AWS CodePipeline, Lambda, etc.
• Develop Airflow DAGs to run training and scoring pipelines
• Develop a Testing framework with Pytest
• Implement monitoring solution with homebrew solution using Lambda and Dash
• Develop Data Quality solutions potentially leveraging Great Expectations.

Requirements

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.

We are looking for a motivated and passionate Machine Learning Engineers for our team.

As part of this job, you will be responsible for:

• Providing solutions for the deployment, execution, validation, monitoring, and improvement of data science solutions
• Creating Scalable Machine Learning systems that are highly performant
• Building reusable production data pipelines for implemented machine learning models
• Writing production-quality code and libraries that can be packaged as containers, installed and deployed

Requirements