A well-experienced Machine Learning and Generative AI Engineer with over 3+ years of industry experience in designing, developing, implementing, deploying, and maintaining machine learning models and advanced AI solutions in production. Proficient at harnessing extensive and complex datasets to derive actionable insights and develop end-to-end solutions tailored to business needs. Passionate about staying updated with industry best practices and committed to continuous learning and development. Excellent problem-solving skills combined with effective communication abilities to collaborate across teams and convey technical concepts to non-technical stakeholders.Technical Skills● Programming Languages: Python (Pandas, NumPy, Matplotlib, Seaborn, Jupyter Notebook), R, Java, OOP ● Generative AI: LangChain, LlamaIndex, Haystack, Hugging Face, Open AI, Open-source, and paid LLM models (Llama2, Mistral, OpenAI, Google Gemini Pro), Chatbot, RAG System● Machine Learning Frameworks: TensorFlow, PyTorch, Scikit-Learn, MLOps● Deep Learning: ANN, CNN, RNN, LSTM, NLP, LLMs, LLMOPs, Transformer Model, Transfer Learning, Fine Tuning, Prompt Engineering.● Database: SQL(MSSQL, MySQL, PostgreSQL), NoSQL( MongoDB, Cassandra)● Vector Database: ChromaDB, Pinecone, FAISS, Weaviate, LanceDB, DataStack.● Big Data Processing: Apache Spark, Data Lakes, Databricks, Data Warehouses, Hadoop, Hive● Statistical Analysis: (R, SPSS, SAS, MATLAB), Statistical Techniques, Probability Theory, statistical modeling● Versioning System: Git, DVC, GitHub, GitLab, Bitbucket, DagsHub, MlFlow● Deployment Frameworks: Docker, Flask, Kubernetes, AWS SageMaker, GitLab CI/CD, GitHub Actions, Jenkins, CircleCI, Terraform, Ansible, Puppet● Monitoring and Testing: Prometheus, Grafana, PyTest, unit Testing● Cloud Platforms: AWS (Amazon Web Services, AWS Bedrock), Google Cloud Platform (GCP), Microsoft Azure, Streamlit, Gradio, Hugging Face Space● Computer Vision and Image Processing Soft Skills● Analytical thinking● problem-solving● Teamwork● Effective communication"Unveiling the depths of your data to reveal profound insights, emerging trends, and intricate patterns empowers you to make informed, high-quality decisions that inspire trust and drive success in your business." - Ayodele Ayodeji
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Development Team LeadDatawoxBenin City, Ed, Ng
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Team LeadDatawox Nov 2023 - PresentIn my role as Team Lead at DataWox, I oversee a team of data annotators, ensuring that all tasks are completed on time and to high-quality standards. I implement quality control processes to guarantee the accuracy of data annotations, aligning closely with client requirements.I work collaboratively with clients to understand their specific needs, ensuring we deliver successful outcomes and maintain strong, ongoing partnerships. I also streamline operations, managing the annotation of bulk datasets efficiently and improving workflows to enhance productivity.
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Machine Learning & Generative Ai Engr.Starwox Jan 2023 - PresentGlasgow, UkResponsibilities:• Managed the Implementation of end-to-end MLOps processes, leveraging GitLab CI/CD, Docker, Kubernetes, and AWS SageMaker, achieving a 30% improvement in model deployment efficiency and generating $15 million in annual revenue growth, showcasing a significant financial impact.• Managed MLOps for a pivotal churn prediction project at Starwox, utilizing TensorFlow, PyTorch, Scikit-Learn, etc. delivering 35% model deployment efficiency boost, $20K annual revenue growth, significant financial impact, and substantial cost savings.• Implemented cutting-edge ML deployment pipelines with TensorFlow, Kubernetes, Docker, Prometheus, Apache Airflow, Github Action, and FastAPI showcasing innovation and cost reduction by 25%.• Developed and deployed a cutting-edge chatbot leveraging Generative AI and RAG system as a knowledge base integrating a Multimodal model to enhance understanding and response accuracy. Achieved 40% improvement in customer query resolution time, increased user engagement by 25%, and reduced operational cost by 20% by automating customer service tasks. Used tools such as LangChain, Llama-Index, Unstructured.io, Hugging Face Transformer, Weaviate, dockers, Kubernetes, CI/CD Pipelines, FastAPI, and AWS.• Continuous Integration/Deployment Pipeline Integration, pull requests, code reviews, load/stress testing, PyTest, and unit testing. -
Machine Learning Engineer(Mlops)Zummey Jan 2022 - Dec 2022Benin City, Nigeria• Implemented customer complaint severity classification at Zummey, leveraging advanced NLP techniques with TensorFlow, PyTorch, and Scikit-Learn. Achieved a 40% efficiency boost, driving a substantial $5M annual revenue increase and delivering impactful improvements in customer satisfaction and issue resolution.• Worked on data engineering tasks, including setting up data pipelines using Apache Kafka and Apache Spark, and ensuring data quality and integrity with tools like Apache Airflow for reliable model training and inference.• Utilized MLOps tools and frameworks, such as MLflow, Kubeflow, and Apache Airflow, to streamline ML workflows and automate repetitive tasks.• Optimized model training pipelines, reducing training time by 20% through efficient data preprocessing and distributed computing on AWS.• Conducted thorough model performance analysis and fine-tuned hyperparameters to achieve optimal model efficiency.• Developed and maintained CI/CD pipelines for seamless deployment of ML models into production environments using tools like Jenkins, GitLab CI, Docker, and Kubernetes, ensuring rapid and reliable updates.• Collaborated with software engineering teams to integrate ML models into production systems and optimize their performance.• Collaborated with cross-functional teams to identify business needs, designed, and implemented deep learning solutions to automate manual processes, resulting in a 50% reduction in operational costs.• Ensured compliance with data privacy regulations (GDPR, HIPAA) and implemented security best practices using tools like HashiCorp Vault and AWS Identity and Access Management (IAM) to safeguard ML workflows and data.
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Data Scientist- InternSafewox Feb 2021 - Nov 2021Texas, United States- Collected and cleaned data from diverse sources to ensure accuracy and consistency.- Conducted exploratory data analysis, identifying patterns, outliers, and trends using Matplotlib and Seaborn.- Collaborated in feature engineering and dataset preparation for modeling.- Supported the development of machine learning models for predictive tasks.- Assisted in model evaluation, fine-tuning, and hyperparameter tuning.- Gained exposure to model deployment and cross-validation.- Contributed to cross-functional data science projects.- Maintained detailed project documentation for clarity.key Achievements:- Improved predictive model, boosting forecasting accuracy by 15%.- Enhanced data accessibility through a data visualization dashboard.
Ayodele Ayodeji Education Details
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Physics
Frequently Asked Questions about Ayodele Ayodeji
What company does Ayodele Ayodeji work for?
Ayodele Ayodeji works for Datawox
What is Ayodele Ayodeji's role at the current company?
Ayodele Ayodeji's current role is Development Team Lead.
What schools did Ayodele Ayodeji attend?
Ayodele Ayodeji attended Udacity, University Of Benin.
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Ayodele Ayodeji
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Ayodele Ayodeji
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