DLabs.AI is an AI software development company that helps businesses grow by uncovering hidden gems in data and automating processes. They offer solutions for marketing, sales, customer service, retail, healthtech, edtech, finance, and manufacturing. Their expertise includes deep learning, NLP, computer vision, RPA 2.0, predictive modeling, machine learning, cognitive computing, and neural networks. They build tailor-made AI solutions that integrate with existing systems and provide ongoing support.
• computer vision
• machine learning
• deep learning
• nlp
• predictive modelling
• cognitive computing
• gpt integration
• rpa 2.0
Machine Learning Engineer
DLabs.AI is an AI software development company that helps businesses grow through AI solutions and data analysis.
Benefits:
Cafeteria system
Clear terms
Flexible hours
Free drinks and snacks
Private health care
Education Requirements:
Master's degree in Computer Science, Mathematics, Physics, or a related field, or equivalent experience
Experience Requirements:
At least 2 years of experience in deploying ML models in production environments and implementing machine learning solutions, with a focus on practical applications
Experience working with at least one cloud platform (AWS - must have, Google Cloud, Azure - nice to have), deploying ML models and ML pipelines in production environments
Experience with orchestration tools (Docker, Kubernetes)
Other Requirements:
AWS Certification
Knowledge of cloud-based data engineering solutions, such as AWS Glue, Azure Data Factory, or Google Cloud Dataflow
Domain expertise in one or more industries, such as edtech, pharma, fintech, retail, and experience in applying ML solutions in those domains
Experience in at least one deep learning framework: Pytorch, TensorFlow / Keras
Demonstrated experience in working with large-scale tabular data that exceeds memory limits
Fair amount of hours spent with DBT, SQL and data warehouses
Previous exposure to business - communicating with stakeholders, gathering requirements for the project, demonstrating project outcomes to clients, supporting decision-making processes in non-tech companies or similar activities
Personal projects, hackathons, summer schools, volunteering, applying ML to your hobby or other initiatives related to AI
Responsibilities:
Driving value-focused AI projects and shaping our evolving tech stack.
Create optimized processes for implementing ML models and monitoring them in a production environment.
Work with our clients to help them do this and build their internal expertise.
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