Becca Steffen’s Post

Hiring an #ML engineer be like: 🕰️2014. #MLOps/ ML engineering was not even a thing... Recruiter: we need someone who can build a logistic regression with scikit-learn. Me: I used a Titanic dataset to build a logistic regression. Recruiter: Welcome aboard! 🕕2024: Me: I've built high-performance machine learing systems, deployed over 100 models to production, and mastered Kubernetes. I'm proficient in AWS, GCP, Azure. I'm skilled in Terraform, CI/CD, Airflow, mlflow, SQL, no-SQL, and Python. On weekends, I'm building my own chatbot. Recruiter: Hmm, I'm not sure that's quite enough... Inspired by a post by Mehdi Ouazza #hiring

Recruiting for talent 🤦🏽♀️, why we stil haven’t nailed it yet! I see many CVs that say “I have experience in Python, R, Scala, Apache, Spark, Hadoop, PyTorch, TensorFlow, Docker, Kubernetes, VSCode, PYCharm, Cursor, HPC, API Toggling, etc”🤦🏽♀️ Then I see corresponding JDs that say we’re looking for an engineer proficient in back-end and front-end development, Ui/Ux, CI/CD, DevOps, GenAI, Robotics, Data Engineering, Data Processing, Data Science … and be wonderful at communicating with business teams and lead a team “ 🤷🏻♀️ It’s important #recruiting teams and those in #talentacquisition understand you can’t hire a person to do the job of a team because budgets are tight. But also, practitioners & managers don’t flood CVs with skills they are not completely proficient in or have the aptitude of strengthening on the job! Just be truthful about what you can do, but you have the potential to do you enjoy! This leads to job satisfaction & happier teams!

AppSierra is hiring through Pitch N Hire N Hire for its client, a skilled ML Engineer. Location: Remote Exp: 3-7 years Apply Here: https://lnkd.in/gqCAbuyD #machinelearning #artificialintelligence #ai #datascience #python #technology #programming #deeplearning #coding #bigdata #computerscience #tech #data #software #dataanalytics #pythonprogramming #developer #datascientist #javascript #programmer #java #innovation #ml #coder #robotics #webdevelopment #analytics #html #linux

When comparing the job ecosystem for AI Engineers at foreign companies (outside Indonesia) or even multinational companies within Indonesia, a significant difference becomes evident. These companies place a strong emphasis on the specialized role of AI Engineers, with a focus on skill sets that are directly related to artificial intelligence. Candidates are often evaluated on their knowledge of Machine Learning (ML) and Deep Learning (DL), their ability to perform Exploratory Data Analysis (EDA), and their experience in model training and research. This contrasts sharply with some local startup environments, where the AI Engineer role can sometimes encompass a much broader range of responsibilities, including Database System Management, Frontend Development, System Integration, and even deploying applications using Docker. The specialized focus in multinational and foreign companies allows AI Engineers to concentrate more deeply on developing and refining AI models, ensuring they stay at the forefront of technological advancements in the field.

Hiring an #ML engineer be like: 🕰️2014. #MLOps/ ML engineering was not even a thing... Recruiter: we need someone who can build a logistic regression with scikit-learn. Me: I used a Titanic dataset to build a logistic regression. Recruiter: Welcome aboard! 🕕2024: Me: I've built high-performance machine learing systems, deployed over 100 models to production, and mastered Kubernetes. I'm proficient in AWS, GCP, Azure. I'm skilled in Terraform, CI/CD, Airflow, mlflow, SQL, no-SQL, and Python. On weekends, I'm building my own chatbot. Recruiter: Hmm, I'm not sure that's quite enough... Inspired by a post by Mehdi Ouazza #hiring

Most recruiting processes today:

Hiring First Data Engineer with Computer Vision experience for an early-stage AI startup. Though we're unable to divulge many specifics at this time, here's what we're searching for: 1. Profound domain expertise in computer vision or diffusion models for visual synthesis 2. Proven experience handling vast amounts of unstructured data, including building efficient and parallelized data pipelines for rapid training data loading and management of terabytes of data 3. Passion for AI in image and video domains 4. Familiarity with fundamental ML models such as K-means clustering, PCA, and experience with pre-trained models 5. Capability to handle the entire spectrum of data tasks from collection, cleaning, and annotation to storage and retrieval 6. Exceptional computer engineering prowess encompassing web engineering and tasks like web scraping 7. Proficiency in programming languages like Python, Java, etc., as well as SQL, big data technologies like Spark, ETL processes, data warehousing, distributed systems, data modeling, version control (Git), containerization (Docker), and cloud platforms (AWS, Azure).

I'm starting to look around for few key hires for the team. If you're interested email: [email protected] * We filled our current threat research position * AI / ML Engineer(s) focused on continuing to build out our AI/ML features and use cases full time with the latest and greatest AI/ML technologies and techniques. Python is a must, and Java would be nice. Must have built production AI/ML features; building out ML applications in streaming systems (similar to Spark, DataBricks, etc.) would be nice. This is more of a deliver things quickly, than research role. These are senior and above roles, preference in the US for the Threat Research role. US or India for the AI / ML roles. We are remote first with slight centers of gravity currently in San Luis Obispo, CA; Pittsburgh, PA; and Delhi, India. We are a true startup: the pace is rapid. flexibility in what you're doing, an extreme orientation towards action + getting shit done, ability to build things from nothing quickly, reverse engineer and adapt to rapidly changing code bases, and a very strong willingness to grind through bugs + troubleshooting in the startup jungle with bold accelerating solutions is so so so key; as there are very few paved paths yet, and doing things that just add another detection rule isn't going to cut that path.

Dear recruiters,  If your AI Engineer job description looks like this 👇, it’s safe to say you’re not hiring one engineer—you’re assembling a Data & AI Justice League! 🦸♂️🦸♀️  I mean, who wouldn’t want a single person who can juggle Python, Kubernetes, Spark, and maybe brew coffee while spinning up an EC2 instance? ☕️🤖  But seriously, let’s cut them some slack—AI engineers are amazing, but they’re not supercomputers (yet).  👉 Follow me for more tech humor and realistic takes on the AI world.   ♻️ Share if you’ve ever seen a job post that made you laugh and cry at the same time!  #AI #DataScience #MachineLearning #Python #TechHumor #CloudComputing #RecruitmentFails #GenAI #EngineeringFun  

We're hiring ML Performance and Developer tooling enthusiasts at the Bay Area and London Google offices! When it comes to expensive ML workloads, every opportunity for performance counts.  Our Org’s mission is to accelerate the ML developer community, both at Alphabet and in the Open Source world, to quickly find performance insights. Are you excited about building developer tools - IDEs, frontends, snappy visualizations to be able to parse and efficiently present large volumes of connected data, in an intuitive way, that causes true user delight? Do you enjoy observing developer behavior and improving the e2e tooling experience to remove all points of friction along the way? Have you previously worked on the internals of frameworks like D3, Vis, Plotly? Are you looking to build company central and highly visible debugging tools used by a large number of internal and Open Source ML developers? Are you looking to make an impact at Alphabet scale by delivering performance opportunities across the company - ML Frameworks (JAX), ML Compilers (XLA), Model Owners, Product Area Leads, Senior Execs to guide business critical decisions? Are you passionate about bringing performance insights to life by building benchmark and visualization tools to reason about performance? Please reach out to me if you answered “yes” to any of the questions above, or have referrals so we can explore matching opportunities at Google. We’re looking for a wide variety of skills spanning background in Computer Architecture, Statistical analysis, Visualizing and presenting high quality insights, Frontend and Backend Engineering. Even if your ML background is limited, it is optional for many roles, and this is a great opportunity if you're looking for exposure to advanced ML development at Google. #DevCommunity #IDE #IntelliJ #OpenSource #vscode #Eclipse #xcode #DataVisualization #ChartJS #D3JS #VisJS #threejs #webdev #gamedev #indiedev #3D #WebGL #typescript #webassembly #wasm #JAX #TPU #GPU #TensorFlow #Numpy #PyTorch #AI #LLMs #Reasoning #MLPerf #mlplatform #deeplearning #hpc #BigQuery #DataAnalysis #Dataviz #jobalert #nowhiring #job #gethired #jobopening #jobfair #recruiting #jobopening #hiring #joinourteam #jobs #jobhiring #jobsearch #jobsearching #jobseekers #hire #opentowork #opentohire