Alfonso Tiscareno’s Post

🚨 I went through more than 100+ Job openings for AI engineer positions and curated the skills asked by 90% of the recruiters 🔥. Here’s what they're looking for: 👇 1. Experience with Generative AI Frameworks (Langchain, Hugging Face, Llama index). 👉 Langchain 🦜 is the most demanded one. 2. Foundational knowledge of Generative AI (how models work, techniques like prompt engineering, multimodal AI). 3. End-to-End Retrieval-Augmented Generation (RAG): Ability to build solid RAG workflows. 4. Ability to fine-tune open-source and closed-source models, including knowledge of LoRA, QLoRA, and quantization. 5. Python is the primary language mentioned in the job listings for generative AI engineering roles 🚀. 6. Familiarity with Cloud Platforms (AWS, Azure, GCP) for model deployment and inference. Specific services like AWS Bedrock and Azure OpenAI are in demand. 7. Good knowledge of Vector Databases is a must for Generative AI engineering roles. 8. Candidate should staying up-to-date on new AI models and integration practices 🧠. Apart from the above, there were other skills mentioned but not emphasized much, such as: Experience with natural language processing (NLP), Machine Learning & Deep Learning. However, a candidate should hold basic knowledge of Deep Learning & NLP. AI engineers are paid a lot these days 💰, If you want to switch job as an AI engineer then these skills must be highlighted on your resume. I keep sharing simplified knowledge on these AI skills, connect with me if you are serious about your growth 🌱. Your support means the world to me! 💖 Like, comment, and share to help fuel my passion for creating meaningful content that help others grow in the AI world. Let's keep this journey going together! 🚀✨ #AI #GenerativeAI #Jobs #Hiring

Are you aiming to become a Machine Learning scientist in a top Silicon Valley firm or building a team of exceptional ML engineers? Here's a concise list of Machine Learning interview questions and answers 2024. Machine Learning (ML), a subset of Artificial Intelligence (AI), plays a pivotal role in predicting outcomes through algorithms that leverage historical data. ML engineers are indispensable across various industries, significantly contributing to organizational growth and enhancing customer experiences. Whether you're a job seeker aspiring for an ML Engineer role or a recruiter striving to find the best talent, this curated list of 40 machine learning interview questions and answers is your go-to resource. These questions span basic to advanced levels, covering the full spectrum of machine learning. This resource is a boon not just for candidates but also for tech recruiters who need to evaluate the skills of potential hires comprehensively. Check out the attached PDF on 40 Machine Learning interview questions and answers 2024. Follow me for more such posts. Repost this to share with your connections as well. #machinelearning #engineer #ai #tech #recruitment #jobseekers

I am very open to AIOps, MLOps job offers. That is that job part where someone gathers and processes the data, and trains the Neural Network. And then tests it. This is that super slow and super complicated part of the work. Which requires great patience, because if you prepare the data in the wrong way, Neural Network will not work. Then the Data Scientist here reads scientific magazines, combines Neural Networks Layers, and tells me what data he needs. Based on the latest arxiv.org Temporal Graphs Neural Networks publications, we can say that the Data Scientist will have to do very heavy coding in the Python too. And testing... 😭 This is where professional programmer has advantage too. The days of the easy Neural Networks are over. I can help here too ;-) #hr #recruitment

Get in touch! Machine Learning Researcher - #London(Greater). To apply, please click the link below #Graphics #NLP #ComputerVision #TechnologyRecruitment #Robotics #ArtificialIntelligence #TechnologyJobs #ImageProcessing #ICResources #DeepLearning #TechnologyCareers #MachineLearning #3DReconstruction #DataEngineering #DataScience #Software #AI

⭐ Machine Learning Engineer Seeking New Opportunities ⭐ As a passionate Machine Learning Engineer with a solid Artificial Intelligence and Data Science foundation, I’m actively looking for a role where I can contribute my skills, determination, and problem-solving mindset. 📌 Key Expertise: - Machine Learning: Computer Vision, Facial Recognition Systems, Hyperspectral Image Analysis - NLP: Fine-tuning Large Language Models (LLMs), Sentiment Analysis, Language Translation Models - Advanced Techniques: Retrieval-Augmented Generation (RAG), Data Augmentation, Synthetic Data Generation using OpenAI APIs - Programming: Python, PostgreSQL, and tools like Visual Studio Code, Jupyter, and Google Colab - Skilled in crafting precise and effective prompts to optimize AI model performance I have hands-on experience developing face recognition systems, building automated report generation solutions, and integrating genre-specific advertisements into media content using multimodal machine learning models. What sets me apart is my ability to think critically and approach complex challenges from different angles. Whether it’s fine-tuning LLMs or creating innovative solutions for media content, I thrive on finding the right answers. I'm constantly learning and staying updated on the latest advancements in AI. I’m excited to apply my knowledge and expertise to solve real-world problems in AI and machine learning. I’m always eager to connect with professionals in the AI and machine learning space and would appreciate any leads or introductions to new opportunities. Your support means a lot during this challenging time. 🙌 #OpenToWork #MachineLearning #AI #DataScience #ArtificialIntelligence #Hiring #ML #NLP #ComputerVision #JobSearch

Hello #connections, I recently attended an insightful webinar on "Demystifying AI Hiring: Practical Insights and Tips for HR and Technical Recruiters." Here are some key takeaways on the State of AI Hiring: - Job postings requiring AI and ML skillsets have grown by 45% year over year. - Currently, 18% of all tech jobs demand AI/ML skillsets, a significant increase from 9% last year. - The demand for AI-related skillsets is evolving rapidly, with employers seeking new skills at a 25% higher rate. - Professionals in AI tech fields, such as Machine Learning engineers, are highly sought after and can earn 10% more than the average tech professional. When hiring for roles like Data Scientists, Machine Learning Engineers, AI Engineers, and others, consider the following criteria: - AI tools and experience: Proficiency with tools like Python, PyTorch, and Tensorflow, along with experience in Large Language Models and model training. - Technical Skills: Knowledge of Neural Networks, natural language processing, predictive modeling, and computer vision is crucial. - Beyond Technical Skills: Look for traits such as strong communication, creativity, curiosity, and a growth mindset. #hr #hrm #humanresource #humanresources #humanresourcemanagement #learning #development #learninganddevelopment #shrm #shrmcp #shrmscp #shrmindia

🚀 Unlock Your Future in AI & ML: Exciting Job Opportunities in 2024! 🚀 Are you passionate about Artificial Intelligence and Machine Learning? 2024 is shaping up to be a breakthrough year for AI & ML professionals, with a plethora of exciting job opportunities emerging across industries. Why AI & ML? Artificial Intelligence and Machine Learning are not just buzzwords; they are transforming the way we live and work. From healthcare and finance to technology and entertainment, AI & ML are driving innovation and creating new career paths. What Roles Are in Demand? Data Scientists Machine Learning Engineers AI Researchers AI Product Managers Data Analysts Robotics Engineers NLP Specialists Key Skills to Stand Out: Proficiency in programming languages like Python and R Strong foundation in mathematics and statistics Experience with ML frameworks such as TensorFlow and PyTorch Understanding of deep learning, neural networks, and natural language processing Problem-solving and analytical thinking Why Join the AI & ML Revolution? High Demand: Companies are actively seeking AI & ML talent to drive their innovation agendas. Competitive Salaries: The demand-supply gap ensures attractive compensation packages. Impactful Work: Contribute to cutting-edge projects that have the potential to change the world. Continuous Learning: The field is ever-evolving, offering endless opportunities for growth and learning. How to Get Started: Update Your LinkedIn Profile: Highlight your AI & ML skills, projects, and certifications. Network with Industry Leaders: Connect with professionals in the AI & ML community to learn about the latest trends and job openings. Stay Informed: Follow AI & ML news, join relevant groups, and participate in webinars and conferences. Ready to embark on an exciting career in AI & ML? Explore job opportunities today and be part of the technological revolution! #AI #MachineLearning #AIJobs #MLJobs #TechCareers #ArtificialIntelligence #JobOpportunities #CareerGrowth

Do you struggle with irrelevant applications when posting Data Science, Analytics, AI, or ML jobs on conventional job boards? Do you receive a flood of resumes, but 95% aren't suitable? Visit Renalytics.com to hire top Data Science, Analytics, AI, ML, & Blockchain talent. #renalytics #DatAnalytics #DataScience #DataManagement #AI #ML #ArtificialIntelligence #MachineLearning #NLP #DataAnalysis #DataJobs #AnalyticsJobs

𝗗𝗶𝗱 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄 𝘁𝗵𝗲 𝗱𝗲𝗺𝗮𝗻𝗱 𝗳𝗼𝗿 𝗔𝗜/𝗠𝗟 𝘀𝗽𝗲𝗰𝗶𝗮𝗹𝗶𝘀𝘁𝘀 𝘄𝗶𝗹𝗹 𝘀𝗸𝘆𝗿𝗼𝗰𝗸𝗲𝘁 𝗯𝘆 𝟰𝟬% 𝗯𝘆 𝟮𝟬𝟮𝟳? 🚀 The surge in AI & ML jobs is reshaping the job market! By 2027, demand for AI/ML specialists is set to soar by 40%, creating 1 million new jobs. These roles advance technologies like natural language processing and fraud detection. Machine learning engineers, pivotal to this growth, earn an average of $133,336 annually. Computer science remains the top degree for these positions, highlighting the need for specialized knowledge. For aspiring ML engineers: 8% of job offers require Python, especially TensorFlow and Keras. And 6% of these roles accept entry-level candidates. With the AI market growing at a CAGR of 38.1%, it's clear the future is bright for AI professionals. By 2025, 97 million people will be part of this dynamic field. How are you preparing for this AI-driven future? Share your thoughts. #AI #ML #jobmarket #technology #NLP #frauddetection #machinelearning #engineers #salary #computerscience #Python #TensorFlow #Keras 𝗧𝗵𝗲 𝗳𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜/𝗠𝗟 𝗹𝗼𝗼𝗸𝘀 𝘁𝗵𝗿𝗶𝗹𝗹𝗶𝗻𝗴! 𝗪𝗵𝗮𝘁 𝘀𝘁𝗲𝗽𝘀 𝗮𝗿𝗲 𝘆𝗼𝘂 𝘁𝗮𝗸𝗶𝗻𝗴 𝘁𝗼 𝗽𝗿𝗲𝗽 𝗳𝗼𝗿 𝘁𝗵𝗲𝘀𝗲 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝗶𝗲𝘀? 𝗦𝗵𝗮𝗿𝗲 𝘆𝗼𝘂𝗿 𝗴𝗮𝗺𝗲 𝗽𝗹𝗮𝗻! Hit like if you're excited about the future of tech