AI Specialist
Job details
BeGig Overview BeGig is a freelancing platform that connects skilled freelancers with global enterprises to deliver innovative tech solutions. We want to transform the way work is done by enabling freelancers to work on exciting projects, collaborate with international companies, and make a significant impact in the tech industry by allowing startups to build on their ideas instantly. Why We’re Building BeGig
- The traditional job market is evolving, and many professionals are seeking flexible work arrangements and diverse opportunities.
- Enterprises are in constant need of top-notch tech talent, and we aim to bridge this gap by offering them access to talent with niche skills.
- We want to eliminate the hassle of outdated hiring processes and empower freelancers and enterprises to connect seamlessly.
- The global gig economy is booming, and we're here to ensure it’s a win-win for both freelancers and businesses.
- Develop and optimize machine learning models (supervised, unsupervised, and reinforcement learning).
- Fine-tune Large Language Models (LLMs) like GPT, BERT, etc., for code generation, semantic search, and conversational AI.
- Implement advanced Natural Language Processing (NLP) solutions, including named entity recognition, sentiment analysis, and tokenization.
- Integrate generative models (GANs, VAEs, diffusion models) into workflows.
- Build multimodal solutions combining text, image, audio, and video using models like CLIP and DALL-E.
- Apply RL techniques (Deep Q-Learning, PPO, A3C) for agent behavior modeling and decision systems.
- Deploy autonomous AI agents using frameworks like LangChain or AutoGPT.
- Deploy AI models on cloud platforms (AWS, GCP, Azure) using Docker and Kubernetes.
- Optimize models for performance and scalability.
- Collaborate with cross-functional teams to align AI solutions with business goals.
- Publish research and stay updated with advancements from organizations like OpenAI and DeepMind.
- Proficiency in Python and at least one deep learning framework (PyTorch, TensorFlow, or JAX).
- Experience with OpenAI APIs, AutoML frameworks, and AI ethics principles.
- Strong communication, problem-solving, and critical thinking skills.
- Experience with MLOps tools and pipelines (e.g., MLflow, Kubeflow).
- Knowledge of distributed computing frameworks (Spark, Dask).
- Contributions to open-source AI projects.
- The flexibility of a freelance role with opportunities to work on diverse AI projects.
- Competitive compensation, based on outcome-based performance.
- A collaborative environment with opportunities to learn from global enterprises and cutting-edge AI research.
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