Job Description:
We are seeking a highly skilled and motivated AI/ML Data Scientist to drive the development, deployment, and optimization of artificial intelligence and machine learning solutions. The ideal candidate will leverage advanced analytical methods, data engineering, and machine learning techniques to solve complex challenges, provide actionable insights, and enhance decision-making processes.
Position Responsibilities:
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Data Exploration & Preparation
- Collect, preprocess, and analyze structured and unstructured datasets.
- Perform exploratory data analysis to identify trends, patterns, and anomalies.
- Work with data engineering teams to design and optimize pipelines for data acquisition and transformation.
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Model Development
- Design, build, and validate machine learning models using supervised, unsupervised, and reinforcement learning approaches.
- Optimize algorithms for scalability, performance, and accuracy.
- Prototype and deploy AI/ML applications in areas like NLP, computer vision, predictive analytics, and recommendation systems.
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Research & Innovation
- Stay updated on the latest advancements in AI/ML research and tools.
- Explore and implement emerging technologies, frameworks, and best practices.
- Conduct experiments to evaluate new algorithms and approaches.
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Collaboration & Communication
- Collaborate with cross-functional teams, including product managers, software engineers, and domain experts.
- Translate technical insights into business value for non-technical stakeholders.
- Present findings, model performance, and actionable recommendations effectively.
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Deployment & Monitoring
- Implement end-to-end AI/ML workflows, from proof-of-concept to production.
- Monitor and maintain model performance, ensuring adaptability to changing data conditions.
- Develop strategies for model explainability and interpretability.
Qualifications:
- Education: Master’s degree in computer science, Data Science, Statistics, Mathematics, or a related field.
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Experience:
- Proven experience in AI/ML model development and deployment (2–5 years preferred).
- Hands-on experience with large-scale datasets and real-world AI/ML applications.
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Technical Skills:
- Strong proficiency in Python, R, or Julia, and ML libraries/frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Familiarity with data manipulation tools (e.g., Pandas, NumPy) and visualization libraries (e.g., Matplotlib, Seaborn).
- Experience with cloud platforms (AWS, Azure, GCP) and containerization (Docker, Kubernetes).
- Knowledge of database systems (SQL, NoSQL) and big data tools (Hadoop, Spark).
- Expertise in algorithms, statistical modeling, and deep learning techniques.
- Experience with Version Control Systems and Collaboration (GitHub, GitLab, Jupyter Notebooks, etc.)
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Soft Skills:
- Excellent problem-solving and critical-thinking abilities.
- Strong written and verbal communication skills.
- Ability to work in fast-paced, collaborative environments.
Preferred Qualifications:
- Experience in natural language processing (NLP), computer vision (CV), or reinforcement learning (RL).
- Familiarity with MLOps tools and practices (e.g., MLflow, Kubeflow).
- Domain knowledge in defense industry.
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