I've been keen to join a company with a strong focus on ML, but finding the right fit, or any fit, has been challenging. Although I'm open to various industries, my background aligns particularly well with Healthcare, Finance, and E-Commerce. My job hunt has been challenging, and I'm wondering if I'm missing something. I'm reaching out here to the Blind community in hopes of gaining some insights or guidance. I see my niche as being a polymorphic engineer, being able to not just build a performant ML model, but supporting the entire full-stack ecosystem that is necessary to bring value to clients, users, and the organization. In addition to my technical skills, I've led software engineering teams, fostering strong team dynamics and creating enduring enterprise solutions. My roles have ranged from Sr. Software Engineer and Principal Software Engineer to leadership positions like Sr. Manager of SRE, VP of Engineering, and Director of Engineering. My expertise extends to both people development and shaping business strategies. I've realized that routine managerial tasks don't capture my true passion and drive. Instead, I thrive when immersed in deep work, whether collaboratively or independently. Background: - Years of Experience (YoE): 20 Qualifications: - International MBA - Almost completed Masters in ML (Current GPA: 3.85) Key Achievements: - Spearheaded a startup team for 15 years as their first employee - Launched my own SaaS product across 8 countries, supporting 4 languages and currencies - Built and deployed my inaugural ML model in 2015, which remains operational Industry Experience: e-Commerce, Healthcare, Finance Technical Skills & Tools: - Programming Languages: Python, PHP - Databases: - RDBMS: MySQL - NoSQL: DynamoDB, Redis - Big Data: BigQuery, Snowflake, Hadoop, Spark - Search Engines: Elasticsearch (Opensearch) - Frameworks: Flask, Laravel (basic knowledge in FastAPI & Django) - Software Architecture: Domain-Driven Design, Clean Architecture, MVC - Frontend: SCSS (BEM), Blade, Vue, Angular, React - API Development: Extensive experience - Microservices: Worked with SOA using Kafka - Cloud Platforms: AWS, GCP - ML Tools: PyTorch, Tensorflow, Keras, FastAi, VertexAI, AutoML, Sagemaker, Colab, Spark, among others. - Data Visualization: Tableau, and various Python libraries (specializing in choropleths and spatial data) Academic ML Projects: - Campaign Contributions Analysis using t-SNE, Hierarchical Clustering, DBSCAN, and XGBoost for predicting state elections. - Malware Detection with data from Android devices, using Hadoop & Spark for feature engineering. - Skin Cancer Image Detection app built with FastAi, deployed via Google Run. - Advanced NLP projects using BERT and FinBERT transformers. - Retail Demand Forecasting using LGBMRegressor. - Deep Reinforcement Learning for Supply Chain Inventory Management. - Explorations in Explainable AI (XAI) using SHAP values. - Document Classification with BERT, PyTorch. - Leadership insights into maintaining model-based solutions and postmortem analysis of Zillow's iBuyer ML product. As my Master's program concludes, I am on track to graduate Summa Cum Laude from a reputable US East Coast institution. I'm currently contemplating specializations in either AI for Healthcare or AI for Finance and would appreciate any insights or feedback on these choices. I've informally advised one of the world's top 10 law firms on their AI policies, thanks to discussions with my partner who's leading the initiative. I've identified some gaps in their legal tech and have advised on team structure and tooling for their objectives, ironically making this 'pillow talk' my most direct involvement with high-profile ML projects. Recently, I've been exploring job opportunities in ML on LinkedIn and the career sections of a few major tech firms. Despite these efforts, I haven't seen much success. The job application process rarely offers feedback, leaving me unsure of my approach. I'm turning to the Blind community for advice: do I need to tweak my presentation, increase my visibility, or simply change my job search strategy? After all, "How we receive feedback is a choice; our response shapes our growth" (Stone & Heen, 2014). Current TC: 190k #machinelearning #artificialintelligence #ml #ai #dataanalytics #datascience #career #advice #sde #healthcare #finance #oracle #microsoft #nvidia #apple #meta #square
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A lot of people here serve money and not God
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Its truly heartbreaking, I can’t work. I can’t focus, isn’t there anyone who can convince Israel to stop Raffah invasion
That's nice you worked with all that but I doubt you have to include all of that in CV, it's just too much, try to pick few major tools you are an expert in. The job market is not the greatest atm, so it might be the factor. How many interviews are you doing a month and which level they are, with such a background I guess it make more sense to apply for more senior level positions like Lead/Staff, it also could be easier to find such high ranking position, because there are just fewer potential suitable candidates for those even on the current market.
In all that verbiage, I don't see any direct ties to impact or value delivery. There's a lot of focus on your individual accomplishments, credentials, and passions, but nothing that demonstrates why they matter. You led and grew a team? Talk about their ROI. You launched your own SaaS product and deployed an ML model? Talk about their impacts. You offered advice on AI policies? Talk about how you influenced key decision makers and spurred them to action. If the style of your resume is reflected here, then I would spend time revising it to focus more on outcomes and results. Also, the job market is challenging for everyone right now, so you're not alone there. If you're at least getting to talk with recruiters, you can always try asking them for feedback as well.
You are omnipotent, you should be the next Elon musk.
i ain't reading allat
Why your tc is so low for 20 yoe? What happened