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Senior AI ML Engineer
2 weeks ago
We are looking for a
Senior AI/ML Engineer
to design, develop, and deploy innovative AI/ML solutions that enhance our products and services. This role involves leading the AI/ML lifecycle from conception to production, collaborating with cross-functional teams, and mentoring junior engineers. The ideal candidate is a hands-on technical expert with strong problem-solving skills and a passion for pushing the boundaries of artificial intelligence.
Roles & Responsibilities:
- Design and develop
scalable AI/ML models and solutions
for integration into existing systems. - Lead
end-to-end AI/ML lifecycle
— from problem definition, data collection, model building, evaluation, and deployment. - Collaborate with
product managers, data scientists, and software engineers
to integrate models into production systems. - Research and implement
state-of-the-art algorithms
to continuously improve performance. - Optimize AI/ML models for
performance and scalability
in cloud-based environments. - Provide
technical guidance and mentorship
to junior team members.
Skills & Knowledge:
- Strong understanding of machine learning techniques and algorithms (regression, classification, clustering, reinforcement learning).
- Proficiency in programming languages: Python, Java, R, PySpark/Scala.
- Experience with ML frameworks and libraries: TensorFlow, PyTorch, scikit-learn, Keras.
- Hands-on expertise with cloud platforms (AWS, Azure, GCP) and deploying AI/ML models in cloud environments.
- Knowledge of big data technologies (Hadoop, Spark) for handling large-scale datasets.
- Familiarity with DevOps practices and CI/CD pipelines.
Requirements:
- 3–5 years of experience in designing and implementing machine learning solutions in a production environment.
- Proven track record of delivering AI/ML projects from concept to production.
- Ability to work collaboratively in cross-functional teams.
Education & Certification:
- Education:
Bachelor's degree in Computer Science, Engineering, Mathematics, or related technical field.
Preferred Certifications:
- Machine Learning or AI certifications (e.g., AWS Certified Machine Learning – Specialty, Google Cloud Professional ML Engineer, Microsoft Certified Azure AI Engineer Associate).
- Big Data or Cloud certifications are an added advantage.