Develop causal inference methodologies to understand true incrementality of product changes ... Proven track record building and deploying ML models in production , particularly in ...
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Develop causal inference methodologies to understand true incrementality of product changes ... Proven track record building and deploying ML models in production , particularly in ...
AI/ML Engineer
Aventura, FL · On-site
We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications ... Build and maintain scalable machine learning pipelines for data processing, training, and inference.
AI/ML Engineer
Aventura, FL · On-site
We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications ... Build and maintain scalable machine learning pipelines for data processing, training, and inference.
We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications ... Build and maintain scalable machine learning pipelines for data processing, training, and inference.
We are expanding our AI/ML capabilities to include generative AI-driven solutions, RAG applications ... Build and maintain scalable machine learning pipelines for data processing, training, and inference.
Review and assess new ML/statistical techniques for practical trading relevance What We're Looking ... Deep knowledge of statistical inference, hypothesis testing, and overfitting risks * Experience ...
Review and assess new ML/statistical techniques for practical trading relevance What We're Looking ... Deep knowledge of statistical inference, hypothesis testing, and overfitting risks * Experience ...
Senior Data Scientist
Fort Lauderdale, FL · On-site
Apply causal inference methods to understand the impact of potential product changes. * Define and build new ML features using text and multimodal embeddings and GenAI. * Validate offline learnings ...
Senior Data Scientist
Fort Lauderdale, FL · On-site
Apply causal inference methods to understand the impact of potential product changes. * Define and build new ML features using text and multimodal embeddings and GenAI. * Validate offline learnings ...
Apply causal inference methods to understand the impact of potential product changes. * Define and build new ML features using text and multimodal embeddings and GenAI. * Validate offline learnings ...
Quick apply
Apply causal inference methods to understand the impact of potential product changes. * Define and build new ML features using text and multimodal embeddings and GenAI. * Validate offline learnings ...
Data Engineer (AI-focused)
Miami, FL · On-site
$90K - $110K/yr
Build and maintain scalable data pipelines for AI/ML use cases * Design data architectures for structured and unstructured data * Prepare datasets for training, fine-tuning, and inference * Ensure ...
Data Engineer (AI-focused)
Miami, FL · On-site
$90K - $110K/yr
Build and maintain scalable data pipelines for AI/ML use cases * Design data architectures for structured and unstructured data * Prepare datasets for training, fine-tuning, and inference * Ensure ...
Principal Machine Learning Engineer
Miami, FL · On-site +1
Strong understanding of inference, latency, scaling, monitoring, and reliability * Strong ML background overall (ML Scientist / ML Engineer trajectory) * Strong coding and engineering skills ...
Principal Machine Learning Engineer
Miami, FL · On-site +1
Strong understanding of inference, latency, scaling, monitoring, and reliability * Strong ML background overall (ML Scientist / ML Engineer trajectory) * Strong coding and engineering skills ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Hands-on experience validating AI/ML models and securing the inference layer. Working knowledge of Identity and Access Management and data security/privacy controls (PHI/PII, encryption). Applied ...
Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...
Explore and evaluate new AI/ML techniques, tools, and methodologies, applying relevant innovations ... and inference efficiency to minimize cost and latency while preserving accuracy. * MLOps ...
Google AI Lead Architect
$52.75 - $72.50/hr
Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...
Google AI Lead Architect
$52.75 - $72.50/hr
Integrate and fine-tune Large Language Models (LLMs) and other AI/ML models into enterprise applications. Develop and implement strategies for model deployment, inference, and monitoring, with an ...
... Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. * Strong understanding of experimental design, statistical testing, and causal inference basics. * Ability to ...
... Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. * Strong understanding of experimental design, statistical testing, and causal inference basics. * Ability to ...
Data Scientist
Miami, FL · On-site
... Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. * Strong understanding of experimental design, statistical testing, and causal inference basics. * Ability to ...
Data Scientist
Miami, FL · On-site
... Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus. * Strong understanding of experimental design, statistical testing, and causal inference basics. * Ability to ...
We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting ... · Membership inference and model inversion testing · Prompt injection and jailbreaking ...
We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting ... · Membership inference and model inversion testing · Prompt injection and jailbreaking ...
Senior Associate, National Security-Cyber Security Governance
Miami, FL · On-site
$95K - $123K/yr
We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting ... • Membership inference and model inversion testing • Prompt injection and jailbreaking ...
Senior Associate, National Security-Cyber Security Governance
Miami, FL · On-site
$95K - $123K/yr
We focus on implementing secure AI/ML pipelines, establishing AI governance frameworks, conducting ... • Membership inference and model inversion testing • Prompt injection and jailbreaking ...
Sr Manager, Data Science
Miami, FL · On-site
... inference, reinforcement learning, or simulation modeling; exposure to LLM-based ML use cases. What we offer: * The opportunity to deliver impact across one of the largest homebuilders in the United ...
Sr Manager, Data Science
Miami, FL · On-site
... inference, reinforcement learning, or simulation modeling; exposure to LLM-based ML use cases. What we offer: * The opportunity to deliver impact across one of the largest homebuilders in the United ...
Associate Director Product Manager
$166K - $265K/yr
While deep subject matter expertise in every pricing, ML, or AI domain is not required, the ability ... Experience with experimentation, A/B testing, causal inference, measurement design, or model ...
Associate Director Product Manager
$166K - $265K/yr
While deep subject matter expertise in every pricing, ML, or AI domain is not required, the ability ... Experience with experimentation, A/B testing, causal inference, measurement design, or model ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Some of the core areas of focus for our team include pricing, online advertising, uplift and long term value modeling, and general causal inference. Search & Discovery ML : The Search and Discovery ...
Ml Inference information
See Miami, FL salary details
$35.9K - $49.7K
2% of jobs
$49.7K - $63.5K
3% of jobs
$63.5K - $77.3K
6% of jobs
$77.3K - $91.2K
9% of jobs
$95.6K is the 25th percentile. Wages below this are outliers.
$91.2K - $105K
15% of jobs
The median wage is $114.2K / yr.
$105K - $118.8K
22% of jobs
$126.4K is the 75th percentile. Wages above this are outliers.
$118.8K - $132.6K
32% of jobs
$132.6K - $146.5K
3% of jobs
$146.5K - $160.3K
4% of jobs
$160.3K - $174.1K
1% of jobs
$174.1K - $187.9K
2% of jobs
$35.9K
$117.4K
$187.9K
How much do ml inference jobs pay per year?
As of Jul 26, 2026, the average yearly pay for ml inference in Miami, FL is $117,392.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,200.00 and $130,100.00 per year, depending on experience, location, and employer.
What is a $900000 AI job?
A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers or AI research directors, often involving advanced skills in deep learning, data modeling, and programming with tools like Python and TensorFlow. These positions usually require extensive experience, specialized knowledge, and may include leadership responsibilities or strategic decision-making.
What is ML inference?
ML inference refers to the process of using a trained machine learning model to make predictions or decisions based on new data. After a model has been trained on historical data, inference is the phase where that model is deployed and used in real-world applications, such as recognizing speech, detecting objects in images, or recommending products. The focus in ML inference is on speed, efficiency, and scalability to ensure quick predictions, often in real time. This process is critical for practical applications like mobile apps, web services, and embedded systems. Optimizing inference involves reducing latency, memory usage, and computational requirements.
What is the difference between Ml Inference vs Data Scientist?
| Aspect | ML Inference | Data Scientist |
|---|---|---|
| Required Credentials | Knowledge of machine learning models, programming skills | Degree in data science, statistics, or related fields |
| Work Environment | Deploying models in production, real-time data processing | Data analysis, model development, research |
| Industry Usage | AI product deployment, software companies | Research institutions, tech firms, consulting |
ML Inference focuses on deploying trained models to make predictions on new data, often in real-time. Data Scientists develop and analyze models, working primarily in research and development. While both roles require understanding of machine learning, ML Inference emphasizes deployment and operationalization, whereas Data Scientists focus on model creation and analysis.
What engineer makes $500,000 a year?
Senior machine learning engineers with extensive experience, advanced skills in deep learning, and expertise in deploying large-scale models can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their specialized knowledge and impact on product development.
Which 3 jobs will survive AI?
Jobs involving Ml Inference, such as data scientists, machine learning engineers, and AI system architects, are likely to persist as they require specialized expertise in developing, deploying, and maintaining AI models. These roles demand critical thinking, domain knowledge, and skills in programming and data analysis that are less easily automated. Continuous learning and staying updated with AI tools and frameworks are essential for these professions to remain relevant.
What are some common challenges faced by ML Inference Engineers when deploying models to production?
ML Inference Engineers often encounter challenges such as optimizing model latency and throughput to meet production requirements, ensuring compatibility with diverse hardware environments, and managing model versioning and updates without disrupting service. Additionally, balancing resource utilization and inference accuracy while monitoring real-time performance metrics is crucial. Collaboration with data scientists, DevOps, and software engineers is typically essential to streamline deployment and maintain robust, scalable inference pipelines.
Will MLE be replaced by AI?
Machine Learning Engineers (MLEs) design, develop, and optimize AI models and systems. While AI automation tools can assist with certain tasks, MLEs are essential for building, tuning, and maintaining complex models, making complete replacement unlikely in the near term. Their expertise in data handling, model deployment, and system integration remains critical in AI development environments.
What are the key skills and qualifications needed to thrive in ML Inference, and why are they important?
To thrive in ML Inference, you need a solid background in machine learning principles, programming (Python or C++), and experience with deploying models at scale, often supported by a degree in computer science or a related field. Familiarity with frameworks and tools such as TensorFlow, PyTorch, ONNX, and cloud platforms like AWS SageMaker or Google AI Platform is typically required. Strong problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and optimizing model performance. These skills ensure efficient, scalable, and reliable deployment of machine learning solutions in real-world applications.
What are popular job titles related to Ml Inference jobs in Miami, FL? For Ml Inference jobs in Miami, FL, the most frequently searched job titles are:
What job categories do people searching Ml Inference jobs in Miami, FL look for? The top searched job categories for Ml Inference jobs in Miami, FL are:
What cities near Miami, FL are hiring for Ml Inference jobs? Cities near Miami, FL with the most Ml Inference job openings:
Full-time
Medical, Vision, Retirement, PTO
Posted 21 days ago
Job description
About CookUnity:
The role:Food has lost its soul to modern convenience. And with it, it has lost the power to nourish, inspire, and connect us. So in 2018, CookUnity was founded as the first-of-its-kind platform that connects the world with the source of truly great food: chefs. Today, CookUnity delivers 50 million meals a year from the industry's best chefs to homes all over the country. Fresh. Ready-to-eat. And crafted with the passion that nourishes body and soul.
Unwilling to stop there, CookUnity is expanding beyond delivery to become an ever-innovating marketplace focused on our singular mission: empower Chefs to nourish the world.
If that mission has you hungry in more ways than one, you've found the right job posting.
We're looking for a Director, Data Science/ML who will drive CookUnity's next phase of product innovation through forward-looking data science capabilities. This role goes beyond traditional analytics—you'll be responsible for building the ML and experimentation foundation that enables personalized, intelligent product experiences at scale.
You'll own the strategic vision for how data science shapes our product roadmap. You'll build and lead a team focused on predictive modeling, personalization, experimentation frameworks, and emerging ML capabilities that directly impact customer engagement, retention, and lifetime value. This is a high-impact role for someone who thinks strategically about the future of product science while remaining hands-on in driving technical execution.
Responsibilities:Strategic Vision & Product Partnership- Define and execute the product data science strategy, identifying opportunities where ML and predictive analytics can unlock step-change improvements in customer experience and business outcomes
- Partner closely with Product, Growth, Engineering, and UX leadership to influence product roadmap with data-driven insights and forward-looking ML capabilities
- Act as a thought leader on emerging data science techniques (personalization, recommendation systems, causal inference, generative AI) and their application to product problems
- Translate complex product challenges into clear data science problems with measurable success criteria
- Own the end-to-end ML lifecycle for product use cases: problem framing, feature development, model training, deployment, monitoring, and iteration
- Partner with the Growth Data Science & Analytics team to align experimentation, measurement, and modeling efforts into a cohesive end-to-end data science ecosystem.
- Build, mentor, and scale a high-performing product data science team capable of delivering both strategic insights and production ML systems
- Foster a culture of innovation, experimentation, and continuous learning within the data science organization
- Create career development pathways that attract and retain top data science talent
- Collaborate with Analytics Engineering to ensure seamless model deployment and monitoring
- Own and evolve personalization and recommendation systems that drive engagement and conversion across the customer journey
- Design and implement robust experimentation frameworks that enable rapid, high-quality product testing and learning
- Develop causal inference methodologies to understand true incrementality of product changes.
- Ensure models are observable, explainable where needed, and continuously improved post-launch
- Define product success metrics and measurement frameworks that align with business objectives
- Build scalable dashboards and monitoring systems that provide real-time visibility into product performance
- Conduct deep-dive analyses on user behavior patterns to uncover opportunities for product optimization
Qualifications:
- 10+ years of experience in data science, with at least 5 years in leadership roles managing data scientists or ML engineers
- Proven track record building and deploying ML models in production, particularly in personalization, recommendation systems, or predictive modeling
- Deep expertise in experimentation and causal inference, including A/B testing, incrementality measurement, and statistical rigor
- Strong product sense and business acumen—ability to identify high-impact opportunities and translate them into data science initiatives
- Experience in consumer tech, e-commerce, or marketplace businesses where personalization and user engagement are critical
- Excellent communication skills—ability to explain complex technical concepts to non-technical stakeholders and influence product strategy
- Hands-on technical proficiency in Python, SQL, and modern ML frameworks (scikit-learn, PyTorch, TensorFlow)
- Experience with cloud-based data infrastructure (AWS, GCP, Snowflake) and ML Ops tools (MLflow, Airflow, Kubeflow)
- PhD or Master's degree in Computer Science, Statistics, Mathematics, or related quantitative field
- Experience with real-time ML systems and feature stores
- Background in recommendation systems or two-tower/multi-modal embeddings
- Familiarity with generative AI and LLM applications in product contexts
- Experience building data science teams from scratch or through periods of rapid growth
- Prior work in subscription businesses or retention-focused products
- Knowledge of modern product analytics tools (Amplitude, MixPanel, Looker)
- 6 months: Established product data science roadmap aligned with business priorities; shipped at least one high-impact ML model to production; built strong partnerships with Product and Engineering leadership
- 12 months: Scaled the product data science function with key hires; delivered measurable improvements in personalization and customer engagement metrics; implemented robust experimentation frameworks used across product teams
Learn More About CookUnity
We believe great leadership starts with alignment on vision, values, and ways of working. To give you deeper insight into who we are and what we're looking for, we invite you to explore: CookUnity's Leadership Principles – The values and behaviors that guide how we operate, collaborate, and scale.
We hope this provides valuable insight into our culture and product vision. If this excites you, we'd love to connect!
Benefits
🩺 Health Insurance coverage
🌅 401k Plan
📈 We grow, you grow: Stock Options Plan granted on Day 1
🌟 Eligible for a bi-annual performance bonus
⛱ Unlimited PTO
🗓️ 5- year Sabbatical: After 5 years with CookUnity, you get a 4-week paid sabbatical
🐣 Paid Family leave
🕯 Compassionate Leave: 3-5 days each time the need arises
🥘 A generous amount of CookUnity credits to enjoy our amazing meals, added to your account, monthly
🧘🏽♀️ Wellness perks: access to fitness subsidies to build a healthy lifestyle
🤖 AI-forward workplace: enterprise access to ChatGPT and Claude to help you work smarter and grow faster.
👩🏾🏫 Personalized Spanish coach
🚀 Awesome opportunity to join a company that is looking to change how we eat and how chefs work!
Compensation All final pay rates will be determined by candidates experience, knowledge, skills, and abilities of the applicant, internal equity, and alignment with market data.
Pay Range for this position
$240,000—$270,000 USD
If you're interested in this role, please submit your application, and if we think you might be a fit, we'll get in touch with you. Thank you for your time!
CookUnity is an Equal Opportunity Employer. We are dedicated to creating a community of inclusion and an environment free from discrimination or harassment. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, age, sexual orientation, gender identity, national origin, citizenship status, protected veteran status, genetic information, or physical or mental disability.
A quick note for all candidates
We've recently seen an increase in recruitment scams across the industry, and we want to make sure you (and your data) stay safe while applying to CookUnity. We also want you to know that we take this seriously — sometimes, as part of our process, we may ask for a brief "proof of humanity" to confirm that we're connecting with a real person, not an impersonator. Here are a few tips to help you protect yourself and know what to expect from us:
- Apply only through our official channels. All open roles are listed on our official careers page: careers.cookunity.com
- Our recruiters are real people — and easy to verify. You can always find them on LinkedIn with verified profiles. If you're unsure, feel free to reach out to us on our official LinkedIn Company Page.
- We only communicate through official CookUnity channels. That means emails ending in @cookunity.com and interviews held through official company platforms (Google Meet or Zoom) — never WhatsApp, Telegram, or SMS.
- We'll never ask for payment or personal financial details. If anyone does, please don't share any information and let us know right away.
If something ever feels off or you're unsure about a message, we'd much rather you double-check with us. You can always contact us directly through any of our social media channels. We appreciate your interest in joining CookUnity — and we care about keeping your experience (and safety) as genuine as possible.