Senior Machine Learning Engineer
- business Talent Job Seeker
- directions_car Islamabad
- workFull-time
Job Title: Senior Machine Learning Engineer Location: Bahria Town, Phase 7, Rawalpindi Employment Type: Full-Time About the Role: We are seeking a Senior Machine Learning Engineer to join our AI/ML team and lead the development of scalable machine learning solutions across multiple domains. You will be responsible for designing, implementing, and deploying models that drive real-world impact. This role requires strong technical expertise, problem-solving ability, and experience in leading ML projects end-to-end. Key Responsibilities: Design, build, and deploy advanced machine learning models and pipelines. Work with cross-functional teams to identify business problems that can be solved using ML. Analyze large, complex datasets to derive insights and optimize model performance. Implement scalable data processing architectures using tools like Spark, Airflow, or similar. Continuously evaluate and improve model accuracy, performance, and reliability. Lead and mentor junior ML engineers and contribute to team best practices. Research and apply the latest ML techniques, including deep learning and generative models. Collaborate with software engineers to integrate models into production systems. Requirements: Bachelor’s or Master’s in Computer Science, Machine Learning, Statistics, or related field (PhD is a plus). 4+ years of experience in ML engineering, including production-level model deployment. Strong proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn, etc.). Hands-on experience with cloud platforms (AWS, GCP, Azure) and ML services. Solid understanding of data structures, algorithms, and software engineering practices. Experience with version control, CI/CD pipelines, and containerization (Docker/Kubernetes). Excellent problem-solving, communication, and leadership skills. Nice to Have: Experience with NLP, computer vision, or generative AI models. Contributions to open-source ML projects or research publications.
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Job ID: 10438774 / Ref: c97ae4baae64ba21699ae657afb3fc66