Machine Learning Engineer

Machine Learning Engineer Developer Jobs

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Machine Learning Engineer

Spectrix Analytical Services, LLC Remote 🌍 Remote

Remote

Today

$48 - $58/hr Contract Artificial Intelligence Aws Ml Cloud Machine Learning

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Job Description

This contract, remote role supports the development and operation of an ML Platform and agentic AI toolchain for protein therapeutic design. The work covers compute infrastructure, MLOps, and agentic capabilities, with end-to-end connections from data and models into downstream analytics in Snowflake.

Key Responsibilities

Develop and maintain production-grade Python services, data pipelines, and command-line tooling.
Build and maintain Helm charts, container images, and the deployment infrastructure used as part of daily delivery.
Deploy and operate Kubernetes workloads across multiple AWS regions and accounts.
Instrument pipelines and models so performance, costs, and benchmark outcomes are measurable.
Collaborate with scientists and engineering leads to determine what to build and help teams adopt new capabilities through documentation and hands-on support.

Required Qualifications

Education and experience aligned to the role: Bachelor’s degree with 7–10 years of relevant experience, or Master’s degree with 5+ years of relevant experience.
Strong Python development skills, with experience building production tooling or production pipelines.
Working knowledge of Kubernetes, Helm, and container-based deployments.
Experience developing, deploying, or optimizing machine learning pipelines in production.
Familiarity with infrastructure-as-code and CI/CD practices.
Experience with AWS, including multi-region or multi-account deployments.
Experience with data warehousing and ELT patterns, with Snowflake preferred.
Experience working on a small engineering team (approximately 3–10 engineers) with end-to-end system ownership and independent prioritization, without dedicated QA, SRE, or release functions.
Routine use of agentic coding harnesses such as Claude Code, OpenCode, Codex, or an equivalent tool as part of day-to-day development, including an understanding of where they help and where they do not.
Willingness to learn computational biology and protein science domain knowledge.
Ability to communicate effectively while working independently in a remote setting and collaborating with both engineers and scientists.

Primary Work Areas

Extend a Kubernetes orchestration platform and the workflows that run on it, including migrating existing application backends onto Kubernetes.
Make the platform region-agnostic so compute scheduling can expand to new AWS regions and accounts through configuration rather than code changes.
Implement model registration, versioning, and serving so model outputs are available to scientific applications and downstream reporting.
Integrate model outputs with the data layer to avoid leaving results as per-project artifacts.
Build automated benchmarking and retraining for computational tools, LLM models, and agent skills used in de novo design, including GPU-backed benchmarking of larger models.
Track test sets and datasets and maintain a persistent record of benchmark results over time.
Incorporate agentic AI into existing scientific applications by defining tools and skills, building evaluation harnesses, and providing safe plumbing for agents to call internal services.
Deliver reliable S3-to-Snowflake data pulls and automated registration of de novo design results, with monitoring and backfill behavior that does not require manual intervention.
Optimize existing production pipelines to reduce runtime and cost through profiling, GPU utilization improvements, batching, scheduling, and container image updates.

Tech Stack

Python
Kubernetes
Helm
Containerized deployments
AWS
S3
Snowflake
CI/CD
Infrastructure-as-code
Claude Code
OpenCode
Codex

Compensation and Employment Details

Job type: Contract
Location: Remote
Compensation: USD 48–58 per hour

Benefits

Automatic benefits for life insurance and short and long term disability insurance
Optional benefits for full time employees: health, dental, and vision insurance
College loan assistance
Employer matched retirement savings plan

Company Overview

Spectrix Analytical Services, LLC provides on-site analytical chemistry services and has delivered reliable, high-quality results since 1999. The team of experienced scientists supports R&D efforts across multiple industries by generating precise analytical data and maintaining sophisticated instrumentation at clients’ laboratories.

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1d ago

Principal Machine Learning Engineer, Platform Integrity Engineering, Level 7

Snapchat Bellevue, WA

Bellevue, WA

1d ago

$235k - $414k/yr Full time Ai Ml Artificial Intelligence Data Science

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Job Description

The Principal Machine Learning Engineer will join Snap’s Platform Integrity Engineering team to design, implement, and scale machine learning models and systems that protect Snapchatters from harmful content and bad actors, while supporting moderation and regulatory compliance.

Location and Work Setup

Bellevue, WA (onsite)
Default together policy: expect team members to work in an office 4+ days per week

Salary and Compensation

USD 235,000 - 414,000 per year
Zone A (CA, WA, NYC): $276,000 - $414,000 base salary range annually
Zone B: $262,000 - $393,000 base salary range annually
Zone C: $235,000 - $352,000 base salary range annually
Equity: eligible for equity in the form of RSUs

Responsibilities

Design, implement, and scale critical machine learning models and systems to protect Snapchatters globally from harmful content and bad actors
Support a healthy content ecosystem through effective moderation and ensure regulatory compliance
Collaborate with cross-functional teams to set and align on machine learning strategies aligned to company objectives
Stay current with advances in machine learning and apply them to solve complex problems with innovative approaches
Partner with leadership to advance the ML tech stack and improve organizational performance
Work across teams to understand product requirements, evaluate trade-offs, and deliver solutions for new products and services
Advocate for best practices across availability, scalability, operational excellence, and cost management
Provide technical direction that influences the broader ML community

Requirements

Bachelor’s degree in a technical field such as computer science, mathematics, or statistics, or equivalent years of experience
9+ years of post-Bachelor’s machine learning experience; or Master’s + 8+ years post-grad ML experience; or PhD + 5+ years post-grad ML experience
2+ years of experience in technical leadership or serving as a domain expert for a technical organization
Experience developing and shipping performant, scalable machine learning models
Experience with TensorFlow, PyTorch, or related deep learning frameworks
Strong understanding of machine learning and deep learning, including computer vision, natural language processing, and LLMs/VLMs approaches and algorithms, with applications to Trust and Safety, Content Moderation, and Content Quality
Experience setting team direction for online machine learning models that proactively detect harmful content and bad actors, moderate content to support a healthy content ecosystem, and automate moderation tasks with high precision
Ability to design, train, and optimize advanced machine learning models
Excellent programming and software design skills
Ability to proactively learn new concepts and technologies and apply them at work
Skilled at solving ambiguous problems and leading and executing complex technical initiatives
Strong collaboration and mentorship skills

Technologies

TensorFlow
PyTorch

Benefits

Paid parental leave
Comprehensive medical coverage
Emotional and mental health support programs
Compensation packages that enable you to share in Snap’s long-term success

Preferred Qualifications

Experience in online safety and integrity, including Trust and Safety, Content Moderation, and Content Quality
Experience developing multimodal models and LLMs/VLMs for harmful content detection, including applying state-of-the-art machine learning techniques to detect bad actors using features such as social, time sequence, and user behavioral signals
Advanced degree in a related field such as machine learning, computer vision, natural language processing, or mathematics
Experience partnering with cross-functional executives and management across a globally distributed organization with sound judgment
Track record of delivery in rapidly changing, highly collaborative, multi-site, multi-stakeholder environments
Experience working with a diverse group of engineers
Experience contributing to AI publications

Education

Bachelor’s degree in a technical field (computer science, mathematics, statistics) or equivalent years of experience.

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1d ago

Machine Learning Engineer Graduate (Conversational AI)

TikTok Seattle, WA

Seattle, WA

1d ago

$122k - $243k/yr Full time Agentic Ai Ai Agent Ai Ml

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Job Description

Machine Learning Engineer Graduate (Conversational AI) at TikTok (Seattle) for a 2027 start, building a self-evolving unified agent system for e-Commerce customer service across 30+ languages.

Responsibilities

Agent runtime (harness / agent loop): Orchestrate skills, tools, and context; implement loop control and intervention; use progressive disclosure and behavior-level guardrails.
Production safety layer: Build pre-flight budgets and timeout truncation; add serve-time gates; deliver shadow and swap-in answers; define safe fallback paths.
Context and memory for long multi-turn agents: Implement agentic memory via structured note-taking; perform context compaction/summarization; support context editing and observation masking; use retrieve-then-load (just-in-time) retrieval.
Post-training and the data flywheel: Apply SFT, DPO, and RL approaches to internalize rules into weights so the prompt gets shorter; distill to smaller serving models; convert served conversations into training, evaluation, and retrieval signals.
Tools, skills, and MCP: Develop tools-as-APIs and connectors; enable skill/tool search across large inventories; govern a skill library (description conflict handling, trigger evaluations, cross-skill mis-fire matrices); load skills on demand instead of dumping all definitions into context.
Evaluation you can bet a launch on: Use LLM-as-judge with human-agreement calibration; apply statistical rigor (paired comparison, confidence intervals, repeated sampling, pass^k); maintain held-out and time-rolling evaluation splits with overfitting alarms; use cascaded scoring and cross-family judge panels to reduce evaluation cost at scale.
Self-evolving loop: Run case mining → automatic root-cause → constrained candidate generation → replay verification against frozen regression sets → canary → data flywheel.
Auditable system plumbing: Maintain a candidate registry with exact runtime read-back, change lineage, and an archive of rejected candidates for sampling in later rounds.
Online experimentation and causal readout: Execute shadow/canary/A-B testing; enforce non-inferiority gates; monitor traffic-split health; define metrics that hold up under scrutiny; apply off-policy counterfactual evaluation when live A/B is not possible.

Requirements

Completed or recently completed a Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related discipline.
Strong Python plus one of: C++, Go, Rust, or Java.
Solid ML/DL/NLP fundamentals with hands-on experience using LLMs or agents through coursework, research, internship, competition, open-source, or a serious side project.
Basic statistical literacy: compute confidence intervals, explain what a p-value does and does not mean, and distinguish “number went up” from “system got better.”
Ability to read a paper or engineering blog and implement working code.

Technologies

Python, C++, Go, Rust, Java
SFT, DPO, RLHF, RLAIF, RLVR
vLLM, TensorRT-LLM, MoE, KV
MCP
A/B, LLM-as-judge
ACM-ICPC, Kaggle

Preferred Qualifications

Built agent runtime functionality beyond calling APIs, even at research/hobby/competition scale (agent loop/harness, memory/context management, RAG or tool-use agent, or fine-tuned/post-trained model).
Hands-on depth in one of the following areas (breadth welcome, depth in one sufficient): post-training (SFT/DPO/RLHF/RLAIF/RLVR, reward modeling, reward hacking and defenses); agent systems (harness, context engineering, MCP/skills, sub-agents, tool search); evaluation/experimentation (LLM-as-judge and calibration, pass^k, regression suites, A/B and non-inferiority testing, off-policy evaluation); self-improving/evolutionary systems (evolutionary search, candidate archives/parent sampling, automatic prompt/context optimization, Pareto selection, credit assignment); inference/serving (vLLM/TensorRT-LLM, MoE, KV/prompt caching, cost engineering); multilingual NLP.
Publications (for PhD), strong competition outcomes (ACM-ICPC / Kaggle / ML competitions), or notable open-source contributions.
Taste for accuracy in metrics and significance, including willingness to communicate when results are not yet significant.
e-Commerce or multilingual experience is a plus (not required).

Benefits

Day one access to medical, dental, and vision insurance.
401(k) savings plan with company match.
Paid parental leave.
Short-term and long-term disability coverage.
Life insurance.
Wellbeing benefits.
10 paid holidays per year.
10 paid sick days per year.
17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).

Compensation

Base salary range (Seattle): $121,600 - $243,200 per year.
Compensation may vary outside the range based on qualifications, skills, competencies, experience, and location.
Base pay is part of the Total Package and the role may be eligible for additional discretionary bonuses/incentives and restricted stock units.

Additional Application Constraints

Must be able to commit to an onboarding date by the end of the year.
State availability and graduation date clearly in the resume.
Apply to a maximum of two positions; applications are considered in the order submitted.
Application limit applies globally for the company and its affiliates.
Reviewed on a rolling basis; apply early.

Location and Role Details

Location: Seattle, WA (onsite).
Employment type: Regular.
Job code: A31120.

Team Introduction

Build a next-generation unified Agent system for TikTok’s global e-Commerce customer service, running in 30+ languages.
North star is a self-evolving agent where post-training, harness, memory/context engineering, tools, and evaluation form a closed loop and each served conversation becomes the next iteration’s training/eval/retrieval/skill-induction signal.
Evaluation and experimentation are treated as first-class systems.
Develop the agent runtime (not prompts on top of a vendor API).
Work includes generative recommendation, large recommendation models, multimodal representation learning, and cross-domain value modeling.

Accommodation and Fair Chance Notices

TikTok provides reasonable accommodations in recruitment for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other reasons protected by applicable laws. Request support at https://tinyurl.com/RA-request.
For Los Angeles County (Unincorporated) candidates: qualified applicants with arrest or conviction records will be considered in accordance with applicable fair chance laws; the company notes that criminal history may have a direct adverse relationship on duties including interacting with internal/external clients/colleagues (occasionally unsupervised), handling confidential information and access to IT systems, and exercising sound judgment.

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1d ago

Machine Learning Engineer - LLMs, Agent Systems, and Simulation Tooling, Siri Core Modeling

Apple Cupertino, CA

Cupertino, CA

1d ago

$150k - $278k/yr Full time Agentic Ai Ai Agent Ai Agent Platform

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Job Description

Join Apple’s Siri organization in Cupertino, CA (onsite) to help define how next-generation intelligent agents reason, plan, and interact through natural voice and multimodal experiences. In this senior Machine Learning Engineering role, you will build scalable LLM reasoning systems and the simulation and evaluation tooling that supports agentic voice capabilities across client and backend environments.

What you’ll do

Design and implement scalable simulation and evaluation frameworks for LLM-based agents.
Develop infrastructure for training and experimentation with agentic behaviors, including how agents plan, adapt, and evaluate actions in realistic environments.
Build scalable evaluation pipelines and create reliable tooling to accelerate iteration for prototyping and deployment.
Integrate agent reasoning capabilities across client-side and backend environments.
Collaborate with ML researchers and applied researchers to translate novel reasoning approaches into production-grade systems.
Run experiments in simulated environments to advance robust, trustworthy agent behavior.

What you bring

Experience deploying LLM models in research or production contexts.
Knowledge of adaptive feedback loops, reinforcement learning, or interactive agent design.
Familiarity with client-backend integration for AI-driven applications.
Strong Python skills (preferred) and proficiency in at least one other programming language.
Proven ML engineering background, including system design, training pipelines, and deployment workflows.
Deep understanding of agent-based simulation, agentic RAG systems, and LLM evaluation methodologies.
Ability to balance long-term platform vision with pragmatic short-term delivery in fast-paced environments.
Minimum education/experience: Bachelor’s degree in Computer Science, Machine Learning, or a related quantitative field, plus 3+ years of relevant industry experience.
Advanced degree preferred: MS or PhD in Computer Science, Machine Learning, or a related field.

Technologies you’ll work with

Python
Reinforcement learning
Agentic RAG systems
LLM evaluation methodologies

Pay & benefits

Base pay range: USD 150,400 - 277,600 per year, determined based on skills, qualifications, experience, and location.

Comprehensive medical and dental coverage
Retirement benefits
A range of discounted products and free services
Reimbursement for certain educational expenses, including tuition
Opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs
Eligible for discretionary restricted stock unit awards
Can purchase Apple stock at a discount if voluntarily participating in the Employee Stock Purchase Plan
Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation

Note: Apple benefit, compensation, and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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2d ago

Gen AI Developer

Realign LLC Richardson, TX

Richardson, TX

2d ago

$105k+/yr Full time Artificial Intelligence Data Pipeline Data Processing

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Job Description

The Gen AI Developer role at Realign LLC focuses on building end-to-end generative AI and LLM solutions, from model design and fine-tuning to deployment, monitoring, and continuous improvement across production applications.

Responsibilities

Design, fine-tune, and deploy generative AI models, including Llama, GPT, and Stable Diffusion, for multiple applications.
Train and optimize large language models for natural language understanding, summarization, and conversational AI.
Develop and maintain robust data pipelines that support both model training and inference workflows.
Clean, preprocess, and manage large-scale datasets used across AI initiatives.
Implement ML models in production environments using tools such as TensorFlow, PyTorch, or Hugging Face.
Optimize models for performance, scalability, and cost-efficiency on cloud platforms including AWS, Azure, and GCP.
Collaborate with product managers, data engineers, and software developers to connect AI implementations to business objectives.
Track and apply advancements in Gen AI and ML research.
Monitor deployed models for performance and accuracy, and implement retraining and versioning strategies.
Ensure deployed systems meet ethical, privacy, and compliance standards.

Requirements

Experience in machine learning, data science, or related fields.
Hands-on experience with generative models such as GANs, VAEs, and diffusion models, as well as LLMs.
Experience with ML frameworks including TensorFlow, PyTorch, or JAX.
Familiarity with cloud environments, including AWS Sagemaker, Azure ML, or GCP AI Platform.
Strong programming skills in Python (preferred) or similar languages.
Proficiency with libraries such as Hugging Face, LangChain, or NVIDIA BioNeMo.
Knowledge of Docker, Kubernetes, and CI/CD pipelines for deployment.
Understanding of NLP, computer vision, or multimodal AI techniques.
Strong problem-solving skills and a passion for AI-driven innovation.
Experience with Retrieval-Augmented Generation (RAG) and vector databases such as Pinecone, Weaviate, or Milvus.

Technologies

Python, TensorFlow, PyTorch, JAX, AWS Sagemaker, Azure ML, GCP AI Platform, Hugging Face, LangChain, NVIDIA BioNeMo, Docker, Kubernetes, CI/CD, Retrieval-Augmented Generation (RAG), Pinecone, Weaviate, Milvus, LLMs, GANs, VAEs, diffusion models, Llama, GPT, Stable Diffusion, NLP, computer vision, multimodal AI

Job Details

Job Type: Full Time
Category: IT
Location: Richardson, TX (onsite)
Salary: USD 105,000 per yearly

Required Skills

Cloud Developer
SQL
Application Developer

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2d ago

Gen AI Developer

Realign LLC Plano, TX

Plano, TX

2d ago

$105k+/yr Full time AI Artificial Intelligence Cloud Platform

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Job Description

Realign LLC is hiring a Gen AI Developer in Plano, TX (onsite) to design, fine-tune, deploy, and support generative AI and LLM solutions.

Responsibilities

Design, fine-tune, and deploy generative AI models for production applications, including Llama, GPT, and Stable Diffusion
Train and optimize large language models (LLMs) for natural language understanding, summarization, and conversational AI
Build and maintain data pipelines that support both model training and inference
Clean, preprocess, and manage large-scale datasets used across AI initiatives
Implement machine learning models in production using TensorFlow, PyTorch, or Hugging Face
Optimize deployed models for performance, scalability, and cost-efficiency on AWS, Azure, and GCP
Collaborate with product managers, data engineers, and software developers to connect AI deliverables to business objectives
Track and apply advancements in Gen AI and ML research
Monitor deployed models for performance and accuracy; execute retraining and versioning strategies
Ensure AI systems meet ethical, privacy, and compliance standards

Requirements

Experience in machine learning, data science, or a related discipline
Hands-on experience with generative models such as GANs, VAEs, and diffusion models, plus LLMs
Experience with ML frameworks including TensorFlow, PyTorch, or JAX
Familiarity with cloud ML environments such as AWS Sagemaker, Azure ML, or GCP AI Platform
Strong programming skills in Python (preferred) or similar languages
Proficiency with tools and libraries such as Hugging Face, LangChain, or NVIDIA BioNeMo
Knowledge of Docker, Kubernetes, and CI/CD pipelines for deployment
Understanding of NLP, computer vision, or multimodal AI techniques
Strong problem-solving skills and interest in AI-driven innovation
Experience with Retrieval-Augmented Generation (RAG) and vector databases such as Pinecone, Weaviate, or Milvus

Salary: USD 105,000 per year

Technologies: machine learning, data science, generative models, GANs, VAEs, diffusion models, LLMs, TensorFlow, PyTorch, JAX, AWS Sagemaker, Azure ML, GCP AI Platform, Python, Hugging Face, LangChain, NVIDIA BioNeMo, Docker, Kubernetes, CI/CD pipelines, Pinecone, Weaviate, Milvus, Retrieval-Augmented Generation (RAG), Llama, GPT, Stable Diffusion, NLP, computer vision

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2d ago

Machine Learning Engineer Graduate (E-Commerce User Growth)

TikTok Seattle, WA

Seattle, WA

2d ago

$122k - $243k/yr Full time Marketing Big Data Data Pipeline

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Job Description

Join TikTok in Seattle for a 2027 start graduate role focused on machine learning for e-Commerce user growth and marketing.

Responsibilities

Optimize TikTok e-Commerce growth and marketing algorithms, including user value modelling, personalized messaging, recommendations, and intelligent marketing.
Build a user lifecycle data and value system to address TikTok Mall user growth pain points and business challenges.
Implement product and technical solutions for user growth engines, including personalized push notifications and emails, recommendation handling, and related components to increase e-Commerce DAU and penetration rates.
Improve recommendation quality for new users by optimizing recall and sorting, including traffic source handling relevance and the accuracy and diversity of new user recommendations.
Advance intelligent marketing algorithms using uplift models and operations research methods to improve marketing efficiency and drive e-Commerce GMV growth.

Requirements

Currently completing or recently completed a Bachelor’s degree in Software Development, Computer Science, Computer Engineering, or a related discipline.
Experience with C++ and Python; at least one Big Data tool such as Hive SQL, Spark, or MapReduce.
At least one Deep Learning tool such as TensorFlow or PyTorch.
Strong foundation in algorithms and data structures with excellent coding skills.
Strong learning ability, curiosity, and good communication and teamwork skills.
Also requires/considers individuals completing or recently completing a Master’s degree in Software Development, Computer Science, Computer Engineering, or a related discipline.
Published papers in top AI conferences or journals, or notable results in ACM/Machine Learning competitions.
Experience in recommendation systems, advertising, user growth, intelligent marketing, or related areas is a plus, including expertise in LTV estimation, uplift modelling, operations research, sequence modelling, or multi-scenario modelling optimization.

Technologies

C++, Python
Hive SQL, Spark, MapReduce
TensorFlow, PyTorch
Uplift models, operations research methods
LTV estimation, sequence modelling, multi-scenario modelling optimization

Benefits

Day one access to medical, dental, and vision insurance
401(k) savings plan with company match
Paid parental leave
Short-term and long-term disability coverage
Life insurance
Wellbeing benefits
10 paid holidays per year
10 paid sick days per year
17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure)
Additional discretionary bonuses/incentives and restricted stock units (role may be eligible)

Team Introduction

The TikTok e-Commerce Recommendation and Marketing Algorithm team delivers algorithm and big data work for e-Commerce innovation projects.
Focus on helping users discover and acquire great products to enrich their lives.
Uses recommendation and search algorithms for item discovery, plus risk control algorithms and intelligent platform governance to detect violations and support a secure shopping experience.
Builds intelligent customer service technologies and large-scale product knowledge graphs to improve transaction process efficiency.
Develops logistics and operations research algorithms to enhance supply chain efficiency and applies AI to help merchants improve operational capabilities.
Mission: make high-quality products easily accessible, enabling everyone to enjoy a better life.

Additional Information

Successful candidates must be able to commit to an onboarding date by the end of the year.
Please include availability and graduation date clearly in your resume.
Applicants can apply to a maximum of two positions and will be considered in the order applied.
Applications are reviewed on a rolling basis; applying early is encouraged.

Pay Transparency

Base salary range (selected city): $121,600 - $243,200 annually.
Compensation may vary based on qualifications, skills, competencies, experience, and location.
Base pay is part of the Total Package.

Los Angeles County (Unincorporated) Candidates

Qualified applicants with arrest or conviction records will be considered in accordance with federal, state, and local laws, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.
The company notes criminal history may have a direct, adverse, negative relationship on job duties, potentially leading to withdrawal of a conditional offer.
Areas cited include interacting with clients or colleagues (occasionally unsupervised), managing confidential/proprietary information, and exercising sound judgment.

TikTok Accommodation

TikTok provides reasonable accommodations in recruitment for candidates with disabilities, pregnancy, sincerely held religious beliefs, or other protected reasons.
Request assistance at: https://tinyurl.com/RA-request