BuzzClan
Website:
buzzclan.com
Job details:
Job Summary:
1. Assist in the design, development, and implementation of AI and machine learning models under the supervision of senior team members.
2. Help collect, clean, preprocess, and analyze large datasets to prepare them for model training.
3. Participate in training, testing, and evaluating AI models, using appropriate metrics to assess performance.
4. Conduct research on current AI trends, techniques, and tools to help the team stay updated.
5. Collaborate with the team to identify business problems that can be solved using AI and contribute ideas for optimization.
6. Support the integration of AI models into existing systems and applications.
7. Document AI experiments, development processes, and results clearly and concisely.
8. Communicate progress and any technical issues to the team in a timely manner.
9. Willing to align with US-hours overlap, with overnights if needed few times a year, flexible for releases over weekends
Technical skills Programming:
Strong proficiency in Python is required, along with experience in languages like Java or C++, and familiarity with other languages like R is a plus. AI/ML Concepts: Solid understanding of fundamental AI and machine learning concepts, including algorithms for classification, regression, and clustering. AI Specialization: Proven experience in one or more areas, including: Natural Language Processing (NLP): Experience with transformers, LLMs, LangChain, and RAG techniques. Computer Vision (CV): Experience with CNNs and tools like OpenCV. Reinforcement Learning (RL): Experience with algorithms like Q-learning and Policy Gradients. Generative AI: Experience in developing and fine-tuning generative models and implementing agentic AI systems. Frameworks & Libraries: Experience with deep learning frameworks such as TensorFlow or PyTorch, and a working knowledge of Python libraries like scikit-learn, NumPy, and pandas. MLOps: Solid understanding and practical experience with MLOps concepts, including CI/CD pipelines, Docker, and Kubernetes. Cloud Platforms: Experience with cloud computing services like AWS, Google Cloud Platform, or Microsoft Azure for deploying and scaling AI models. Data and Databases: Experience with data processing libraries like PySpark and big data technologies such as Hadoop. Knowledge of SQL and NoSQL databases. APIs: Experience designing and developing APIs (e.g., using Flask or FastAPI) to serve AI models. Data Handling: Hands-on experience with data manipulation and analysis is essential. Specialization (Nice-to-have): Familiarity with specific AI domains like Natural Language Processing (NLP), Computer Vision (CV), or Generative AI is a plus. Cloud (Nice-to-have): Exposure to cloud platforms like AWS, Google Cloud Platform, or Azure is beneficial.
Non-technical (soft) skills
Problem-Solving: Strong analytical and critical thinking skills with a detail-oriented approach. Communication: Good verbal and written communication skills to effectively collaborate with team members. Teamwork: Ability to work effectively in a collaborative environment and contribute meaningfully to team projects. Proactiveness: A curious, self-motivated attitude with a passion for continuous learning in a fast-paced environment. Adaptability: Eagerness to learn new technologies and apply them to novel problems.
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