ML Engineer
Job Opening
Machine Learning Engineer
Remote
Full time
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About the Role
We are hiring a Machine Learning Engineer to build and productionize models that power real product features. You will own the lifecycle from data to deployment including problem framing, modeling, evaluation, and maintaining systems in production.
Responsibilities
Work with product and engineering to define machine learning problems and success metrics.
Build, train, and evaluate models for use cases such as ranking, recommendation, classification, forecasting, or natural language processing.
Design and implement data pipelines for feature generation, training, and batch or online inference.
Deploy machine learning models into production services and monitor their performance, drift, and reliability.
Collaborate with software engineers to integrate models into user facing products and internal tools.
Run experiments such as A or B tests and offline or online evaluation and communicate results clearly.
Document assumptions, trade offs, and model behavior for future maintainability.
Stay current on ML tooling and best practices and bring pragmatic improvements into the stack.
Requirements
3+ years of experience in machine learning, data science, or related engineering roles.
Strong programming skills in Python and familiarity with machine learning libraries such as PyTorch, TensorFlow, or Scikit learn.
Experience taking at least one machine learning system from prototype to production.
Solid understanding of core machine learning concepts including supervised learning, evaluation metrics, and overfitting.
Experience working with relational databases and data processing tools such as SQL and Pandas.
Comfortable working with version control, code reviews, and collaborative engineering workflows.
Ability to explain complex technical topics in simple terms to stakeholders.
Nice to Have
Experience with MLOps tooling such as MLflow, Weights and Biases, Kubeflow, or SageMaker.
Experience with language models and modern NLP including embeddings, retrieval augmented generation, fine tuning, and evaluation.
Familiarity with experiment design and A or B testing at scale.
Background in statistics or a related quantitative field.
Important Note
This posting represents the type of full-time role you can be placed into with one of our partner companies after completing the Nairon program.
How it works
1. Apply to join the Nairon Cohort in Dubai
2. Complete screening, hackathons, and the 8-week intensive program
3. Get matched and placed into a position like this one with a Nairon client
Background in data science or machine learning is a plus but not required.
You are not applying to work inside Nairon. You are applying to our training and evaluation program. Based on performance, you may be hired by one of our partner companies and placed into a role similar to the one described here.
Apply for this position