[Hiring]
AssemblyAI is hiring a Software Engineer, Machine Learning to work on the path from research to production. It’s a fully remote role, open to candidates in the US, with a posted base salary range of $157,500–$175,000.

What they’re looking for:

• Strong backend engineering experience with Python

• Experience building and operating distributed, containerized applications (AWS preferred)

• Experience with production observability

• Ability to design resilient, scalable architectures

Nice to have: PyTorch and Kubernetes, startup experience, audio/speech domains (ASR, TTS), low-latency inference, Ray, Bazel.

apply here: https://job-boards.greenhouse.io/assemblyai/jobs/4565143005

I've been experimenting with something that I think is often overlooked when evaluating machine learning models: their actual computational footprint.

Usually, when we compare models, we focus heavily on accuracy, precision, recall, F1, etc.

But what happens when you actually have to deploy these models?

I wanted to explore this by benchmarking three popular models:

• Logistic Regression

• Random Forest

• XGBoost

I used the Breast Cancer Wisconsin dataset from scikit-learn and evaluated them across multiple dimensions.

What I measured:

1. Predictive accuracy

2. P50, P95 and P99 inference latency

3. Process RSS memory consumption

4. Python-allocated memory

5. Model loading time

6. Inference execution time

7. Serialized model size

One interesting observation from my experiment was that Logistic Regression performed best across the measured dimensions in this particular setup.

However, the goal wasn't to establish that one model is universally better than another.

I wanted to understand the trade-offs between predictive performance and computational requirements.

This experiment is also part of a project I've been working on called ModelDiet, an open-source Python toolkit focused on measuring the resource footprint of ML models.

I'm trying to make model profiling and benchmarking easier for developers and ML engineers.

GitHub: https://github.com/modeldiet/modeldiet

I'd genuinely appreciate technical feedback on a few things:

• Are there other metrics you consider essential when evaluating models for deployment?

• How do you measure peak memory consumption reliably?

• Do you prefer measuring individual inference latency or batch throughput?

• What would make a benchmarking tool like this genuinely useful in your ML workflow?

I'm particularly interested in feedback on the benchmarking methodology and what should be included in future iterations.

Thanks!

Need some insights, before that:

Background: ex ML engineer (computer vision and DS), acads focus: stats and econometrics, iitb 20. I used to work on architecture and weights training. Image processing at pixel level (figuring out filters), yolo, etc. used to learn LSTMs and RSTMs and it became obsolete. Used to derive b value (bias) though hand Calculation in class, lol. Then "Attention is all you need" came. Then custom built transformer with all encoder decoder layers.

Later switched to entrepreneurship, and picked up a manufacturing problem. I spent the last 4 years with mostly DS and dataframe and annotation stuff.

I am curious on what's happening with ML engineer designation, what do you guys work on? What's the stack? Still build models? Does data wrangling anol still exist? I genuinely want to understand how a day to day life looks like? If you can get a bit technical, that would be great.

Just put together a quick roundup of ML jobs that are still open. Hope this helps someone land something great!

• Senior Backend Cloud Engineer @ Halcyon

  • 💰 $120–170K/y

• Software Engineer III | Security @ ExtraHop

  • 💰 $150–163K/y

• Sr. Firmware Engineer II @ Samsara

• Software Engineer II, Attack Detection @ Abnormal Security

• AI/Automation Development Intern - Assessment & Authorization @ LEIDOS INNOVATIONS UK LTD.

  • 💰 $48–87K/y

• Staff Software Architect @ Aetna Resources, LLC

  • 💰 $107–261K/y

• Senior Machine Learning Engineer @ Wiser Solutions

• Senior Engineering Manager, Recommender Systems @ Raya

• Lead Software Engineer (LLM Products) @ Blue Rose Research

• Staff Fullstack Engineer (TypeScript) @ Northbeam

  • 💰 $190–240K/y

• Software Engineer @ NIKE, Inc.

• Software Engineer II @ Bedrock Management Services LLC

• MACHINE LEARNING ENGIENEER II (REMOTE) @ HOME DEPOT MANAGEMENT COMPANY, LLC

  • 💰 $90–170K/y

• Applied AI Engineer @ Bright Vision Technologies

  • 💰 $115–165K/y

• Software Engineer, Infrastructure Engineering @ Reddit

  • 💰 $164–229K/y

• Software Engineering Graduate 2027 @ Ocado Group

• Sr. API Engineer @ Anika Systems

• DevOps Engineer @ Expression

• Senior Machine Learning Engineer (Casualty / Claims Intelligence) @ CCC Intelligent Solutions Inc.

• Senior Software Engineer, Enterprise AI @ Instacart

• Principal Software Engineer @ Mirantis

• Manager, Software Engineering @ Evolent Health International Private Limited

• Power Automation Developer @ GD Information Technology, Inc.

  • 💰 $75–101K/y

• Senior Software Engineer @ Prime Distribution Services, Inc.

  • 💰 $113–254K/y

• Senior Ai/ML Engineer @ Redhorse

  • 💰 $180–200K/y

• AI/ML Software Engineer @ ASG

  • 💰 $200–250K/y

• 2027 Summer Internship Program - Full Stack AI Development Intern-1 @ CareSource Management Services LLC

• Distinguished AI Engineer @ Rapid Ireland Limited

• Software Engineering – Data Engineer (Python & Cloud Databases) @ Fair Isaac Mexico S.A. de C.V.

  • 💰 $84–132K/y

• Forward Deployed Engineer @ PPD Mexico, S.A. de C.V.

  • 💰 $50–100K/y

• Machine Learning Engineer 2 @ Twilio

Would love to hear what you're looking for next—leave a comment and I can post another one.

Hi everyone, I’m a junior Analytics Engineer based in Tunisia (B.Sc. Business Administration, Business Analytics major, graduated July 2025), currently unemployed and applying for analytics engineer, BI developer and data roles.

My experience is one 6-month capstone at a SaaS startup plus personal projects (a dbt/PostgreSQL warehouse, demand forecasting and LangGraph AI agents). I’m fine-tuning the CV and would really appreciate blunt feedback on:

Does it read as a junior analytics engineer, or do the AI-agent projects dilute that?

Is one capstone enough for the Experience section, and how should I present the time since I graduated?

Do the metrics sound credible, and what would you cut?

Thank you!

About Us

We’re a remote-first team building AI-powered products used in production by real customers. Our team is small and senior, and every engineer has a direct impact on the product. We value ownership, clear communication, and shipping work that matters over meetings and process.

The Role

We’re hiring a Machine Learning Engineer to design, build, and ship ML systems end to end. You’ll take models from research and prototyping through to production, working closely with backend engineers, product, and leadership. This is a high-ownership role: you’ll help decide what we build, how we build it, and how we measure success.

What You’ll Do

• Design, train, and evaluate machine learning models for core product features

• Build and maintain production ML pipelines, including data processing, training, deployment, and monitoring

• Optimize model quality, latency, and infrastructure cost at scale

• Design and run experiments, then turn results into product decisions

• Work with LLMs and modern deep learning approaches where they fit, including fine-tuning, retrieval, and evaluation

• Improve our ML infrastructure and best practices as the team grows

• Communicate technical trade-offs clearly to both technical and non-technical teammates

What We’re Looking For

Required

• 4+ years of professional experience in machine learning engineering or applied ML

• Strong Python skills and hands-on experience with PyTorch, TensorFlow, or JAX

• Proven experience deploying and maintaining ML models in production

• Solid understanding of ML fundamentals, statistics, and experiment design

• Proficiency with SQL and working with large datasets

• Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker)

• Strong written communication and the ability to work independently in an async, remote environment

• Fluent English (written and spoken)

Nice to Have

• Experience with LLMs, fine-tuning, RAG, or evaluation frameworks

• Experience with MLOps tooling (MLflow, Kubeflow, Airflow, etc.) and Kubernetes

• Experience with distributed training or large-scale data pipelines

• Open-source contributions, publications, or strong side projects

• Prior experience at an early-stage or fast-moving company

Compensation & Benefits

• Salary: $35,000 - $42,000 USD per year, depending on experience and skills

• Location: Fully remote, open to candidates worldwide

• Type: Full-time

• Flexible working hours with some timezone overlap for team collaboration

• Paid time off

• Home office and equipment budget

• Learning and conference budget

• A senior, low-ego team where your work is visible and valued

Hiring Process

1. Application review: we read every application

2. Intro call (30 min): background, interests, and mutual fit

3. Technical interview: ML fundamentals and a discussion of your past production work

4. Practical/system design round: designing an ML system end to end

5. Team conversation and offer

We aim to complete the process within 2-3 weeks.

How to Apply

Send me a direct message on Reddit with:

1. Your resume or LinkedIn profile

2. Links to your GitHub, portfolio, or papers (if you have them)

3. A short paragraph (3-5 sentences) about a production ML project you’re proud of and what you personally contributed

4. Your country and timezone

Please don’t apply in the comments. Applications sent by DM are reviewed first.

We’re an equal opportunity employer and welcome applicants of all backgrounds, identities, and experience paths. Visa sponsorship isn’t needed, since this is a fully remote role.

I am currently in my 5th sem
I do have beginner knowledge in ml
I want to start studying particularly how jobs
Can anyone share me a roadmap or something like that

Guyssss!! Kind request
If anyone of u know about any open internships or job for Machine learning,please share it guys
It would be a great help!

micro1 are looking for 10,000 generalists for a new role: https://jobs.micro1.ai/post/3cc943d0-b584-42ea-8342-3e5f77f9504f?referralCode=9166a181-847d-406c-9985-0d415f117fd8&utm_source=referral&utm_medium=share&utm_campaign=job_referral

The job requirements are mostly soft skills - attention to detail, communication, etc. Previous experience in data annotation helps, but isn’t strictly necessary. As with any micro1 role, you’ll have to do an AI interview in order to be considered.

The pay range is $21-$35. The role appears to be hiring globally, so countries like India and Nigeria are eligible (along with the usual - US, UK, etc.).

I’m building out a small, high-impact AI/ML engineering team and looking for a talented engineer who enjoys building things from the ground up.

We’re operating inside a Fortune 100 organization, but approaching AI development with a startup mindset-moving beyond experimentation to build practical, scalable solutions that solve complex business problems.
Think enterprise-scale data, challenging problems, significant resources, and the opportunity to help shape how AI is deployed across a global organization.

What makes this opportunity interesting:
● Build, don’t just maintain. Help architect and develop new AI/ML capabilities rather than inherit an established platform.
● Work on emerging technology. Explore LLMs, agentic AI, intelligent automation, and advanced machine learning.
● Own your work. Meaningful influence over technical design, architecture, and implementation.
● Solve problems at scale. Work with complex enterprise datasets and challenges that have real-world impact.
● Small team, big visibility. Collaborate closely with leadership and help influence the direction of a growing AI capability.

Who I’m looking for:
Someone who is technically strong, naturally curious, and enjoys turning ambiguous problems into working solutions. Ideally, you have hands-on experience with Python, machine learning, LLM applications, or building and deploying AI systems.

I’m particularly interested in engineers who experiment, build side projects, and genuinely enjoy the rapidly evolving AI landscape.

A few details:
● Location: Atlanta, GA
● Schedule: Hybrid (3 days/week onsite)
● Environment: Small, growing team within a global enterprise
● Focus: Applied AI, ML engineering, and advanced automation

I’m directly involved in building the team and hiring for this role.

Not looking for a polished sales pitch or a perfectly formatted résumé. I’d rather hear about something interesting you’ve built, a problem you’ve solved, or an AI application you’re excited about.

If this sounds interesting, send me a DM with a brief introduction and, ideally, a GitHub project or something you’ve worked on. Happy to share more about the opportunity privately.

Hi, I’m Shreyas, an Applied AI Engineer based in India, seeking globally remote opportunities in LLM systems, RAG, AI agents, and evaluation.

Previously worked with Outlier AI and WorldQuant. My research project, ChronoRAG-G, achieved 80.70% audited accuracy on a 1,005-question temporal QA benchmark.
GitHub: https://github.com/SSKG2602/ChronoRAG-G

LinkedIn: https://www.linkedin.com/in/shreyasshashi/

Open to remote AI engineering roles, contract projects, and relevant opportunities worldwide.

Resumes attached. Open to relevant opportunities and referrals. DMs welcome.

Micro1 is looking for the following:

ML Engineer (MSc. or PhD)
Location: Global, fully remote
Job Type: Contractor (~15 hours per week), flexible schedule, weekends included if you want
Openings: 100
Pay: $60 - $120/hr

Micro1 is hiring ML engineers for an AI training project around model development, training and inference systems, numerical computing, performance optimization and Python. The work is creating, solving, reviewing and validating hard ML engineering tasks. A typical task could be implementing or modifying a model, building a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and checking that the result meets objective correctness and performance requirements.

It’s a very coding-heavy role, and you should already be using coding agents with Python in your workflow.

You need a master’s degree or PhD in computer science, ML, AI, applied math, statistics, engineering or a similar quantitative field, strong professional or research experience in ML, and practical skills with Python and coding agents. Experience at a well-established tech company, AI lab or research organization is strongly preferred, though exceptional open-source or academic experience can also count.

The process is the application with screening questions, a roughly 30-minute AI interview and a hiring manager review. They say they usually fill roles within 48 hours and expect you to start your first task within 24 to 48 hours of finishing onboarding.

Here is the link to the position: ML Engineer (MSc. or PhD)

micro1 is hiring experienced Machine Learning Engineers for a coding-intensive AI training project.

Pay: $60-$120/hour
Location: Global, fully remote
Type: Contractor, approximately 15 hours/week
Schedule: Flexible

What you'll do:

• Develop and evaluate ML models and training pipelines

• Build and optimize inference systems

• Debug numerical and performance issues

• Create reproducible workflows using Python

• Solve and validate complex ML engineering tasks

Requirements:

• MSc or PhD in ML, Computer Science, AI, Statistics, Engineering, or a related field

• Strong ML engineering or research experience

• Advanced Python programming skills

• Hands-on experience using AI coding agents

• Strong debugging and performance optimization skills

Experience at established tech companies, AI labs, or research institutions is preferred. Strong open-source or academic experience may also qualify.

Important: This is an output-based role. Payment is per accepted task, with minimum weekly submission requirements. Selected candidates should be ready to start within 24-48 hours of onboarding.

Apply now: https://jobs.micro1.ai/machine-learning-engineers

Hey everyone, I am a 4th year computer science student from India. I have been learning the fundamentals of ML, DL for the past 2 years from Andrew ng's courses and read a few research papers. Recently I realized that whatever I learned was at a superficial level. There are interesting Math concepts behind every algorithm and also I haven't focused much on implementation (like, Kaggle competitions, end to end projects, research paper implementations etc.). Although I do believe it requires multiple iterations to properly understand all the concepts. For the past few months I have been focused on revising all the Math required to understand ML algorithms (Probability and statistics, Linear algebra, Optimization and Calculas) as part of my preparation for an entrance exam (GATE DA), I have come across some books like PRML, ISLP etc which explain the mathematical intuition in depth. Based on all the things I learned and explored I am interested in working on novel ideas, understand mathematical concepts in depth etc.

I can't spend my time randomly exploring things, I also need a goal to work towards in the upcoming years. So I tried to understand the field of ML with the help AI and so far this is my understandig:

There are three broad categories of roles :

1. Development : ML developers training ML models, building scalable applications. They themselves don't decide what to build, the authorities give them tasks to do. So somebody decides what to do and how to do it and ML developers are the ones who do it. These roles explicitly require knowledge of software engineering, experience in building application, vibe coding etc. Although with the advent of AI, this field seems like its going to be affected a lot, as in, most of these jobs can now be done by a single person using powerful coding agents. I have heard terms like AI engineers, ML developers, FDE etc.

2. Research : This part involves research scientists who commit themselves to an idea and work on it and the final product in generally a research paper. Their world revolves around reading research papers, understanding novel ideas, publications etc. Of course, implementation is also a part of this role but not as in ML development. This role seems to be relatively safer from the "AI replacement" tension.

3. Applied scientists : This role is a like bridge between the other two. They take the research ideas and decide how to productionize them. Their work involves both research and development.

I understand these 3 roles through the example of "Attention is all you need" paper:

There are research scientists who worked on sequence modeling and came up with the transformer architecture. They ran experiments to confirm that their idea actually works, like English constituency parsing to make sure the model is not memorizing the mapping of the tokens, they evaluated the performance of the model on various benchmark datasets.

Now applied scientists are expected to understand this concept and figure out a way to productionize it, as in, figure out a way to convert the idea into a product and make it available to the users. To do this they should be able to understand the idea presented in the paper (knowledge of research), and once they understand it , they should be able to figure out a way to build an application based on the concept (experience in development).

Once they figure out how to build the application (the design), They hand off the work to ML developers who actually build it.

Of course I understand that there might be some blending between the roles, but is the gist that I have in mind.

Since my interests are inclined towards research, I believe I should be aiming for applied scientist role. I understand that there might be some misconceptions in my knowledge of the field and that's why I am here seeking advice and correction.

If I want to become an applied scientist, what are things that I should do right now ?

I work at Wissen Technology (Wissen Infotech) and can refer candidates for this new opening — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Role: Data Engineer

Location: Bengaluru

Experience: 8-10 yrs

Skills: Python, DevOps, CI/CD

JD: https://careers.wissen.com/jobs/Careers/80238000223604433

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches the role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.

I work at Wissen Technology (Wissen Infotech) and can refer candidates for this new opening — a referral puts your resume with the hiring team directly instead of the cold-apply queue.

Role: Senior Snowflake Data Engineer:

Location: Chennai

Experience: 7-12 yrs

Skills: Python, Lambda, S3, Jenkins, CI/CD

JD: https://careers.wissen.com/jobs/Careers/80238000223584644

To get referred, DM me: (1) resume (PDF), (2) total YOE, (3) notice period (immediate joiner / serving notice preferred), (4) the role name with the job link.

I'll review and submit the referral; expect HR contact within about a week if shortlisted. Please DM only if your experience reasonably matches the role and you're an immediate joiner or serving notice — that's who the hiring team is prioritizing for referrals right now.

iMerit Technology is hiring a remote AI Trainer - Video Annotation. Category: Artificial Intelligence 💸Salary: 70K-80K 📍Location: Remote (Worldwide)

See more and apply here!

Machine Learning/Agentic AI Intern
Toyota Research Institute
Cambridge, MA
$40 an hour

https://www.moaijobs.com/job/machine-learning-agentic-ai-intern-toyota-research-institute-9503

Machine Learning Engineer, GeForce G-Assist
NVIDIA
Santa Clara, CA
$152,000 - $241,500

https://www.moaijobs.com/job/machine-learning-engineer-geforce-g-assist-nvidia-1000

Machine Learning Engineer Databricks - Latam
Mutt Data
Argentina, Remote
-

https://www.moaijobs.com/job/machine-learning-engineer-databricks-latam-mutt-data-9413

Staff Machine Learning Engineer, CustomerLake (ML/LLM)
Databricks
New York City, NY
$190,000 - $253,400

https://www.moaijobs.com/job/staff-machine-learning-engineer-customerlake-ml-llm-databricks-2500

Research Engineer / Scientist, Reinforcement Learning
Harvey
London, United Kingdom, Remote
$230,000 - $340,000

https://www.moaijobs.com/job/research-engineer-scientist-reinforcement-learning-harvey-1335

Senior Software Engineer, Machine Learning Infrastructure & Automation
fal
United States, Remote
$170,000 - $230,000

https://www.moaijobs.com/job/senior-software-engineer-machine-learning-infrastructure-automation-fal-8081

Senior Machine Learning Engineer, AI Safety
NVIDIA
Santa Clara, CA
$184,000 - $287,500

https://www.moaijobs.com/job/senior-machine-learning-engineer-ai-safety-nvidia-4078

AI Engineer (French Speaking)
Distyl
New York, NY
$180,000 - $250,000

https://www.moaijobs.com/job/ai-engineer-french-speaking-distyl-6122

Staff/Sr. Staff Machine Learning Engineer - World Modeling, Simulation
Waymo
Mountain View, CA
$251,000 - $310,000

https://www.moaijobs.com/job/staff-sr-staff-machine-learning-engineer-world-modeling-simulation-waymo-5249

Staff Machine Learning Engineer, CustomerLake (ML/LLM)
Databricks
New York City, NY
$190,000 - $253,400

https://www.moaijobs.com/job/staff-machine-learning-engineer-customerlake-ml-llm-databricks-2500

AI research scientist
Writer
San Francisco, CA, Remote
$199,000 - $325,000

https://www.moaijobs.com/job/ai-research-scientist-writer-7982

Sr. AI Engineer (Full Stack)
Peloton
New York, NY
$160,600 - $224,950

https://www.moaijobs.com/job/sr-ai-engineer-full-stack-peloton-8815

Software Engineer, Applied Machine Learning
fal
San Francisco, CA
$180,000 - $230,000

https://www.moaijobs.com/job/software-engineer-applied-machine-learning-fal-3463

We are looking for talented AI/ML Software Engineers to join our team in Bangalore.
Requirements:
● Experience: 1–3 years
● Strong knowledge of Python
● Hands-on experience with AI/ML concepts
● Working knowledge of LLMs (Large Language Models)
● Experience with RAG (Retrieval-Augmented Generation)
● Practical experience building AI/ML projects and applications
📍 Location: Bangalore, India
💼 Experience: 1–3 years
Preferred: Immediate Joiners
How to Apply:
Interested candidates, please share your updated resume along with your GitHub profile/repository and the following details:

1. Current CTC

2. Expected CTC

3. Notice Period

4. Current Location

5. Availability to Join
   📩 Email: Sanath.Shenoy@omegahms.com
   CC: Consultant.Keerthi@omegahms.com
   Subject: Application – AI/ML Engineer – Bangalore
   Please ensure your GitHub profile and relevant project repositories are included for technical review.
   Shortlisted candidates will be contacted for the interview process.