Software Engineer: ML Optimization Job at Generalist AI (San Mateo)

Senior Software Engineer - Network Enablement (Applied ML)

We build simple yet innovative consumer products and developer APIs that shape h...

Location

United States , San Francisco

Salary:

180000.00 - 270000.00 USD / Year

Plaid

Expiration Date

Until further notice

Requirements

Strong software engineering skills including systems design, APIs, and building reliable backend services (Go or Python preferred)
Production experience with batch and streaming data pipelines and orchestration tools such as Airflow or Spark
Experience building or operating real-time scoring and online feature-serving systems, including feature stores and low-latency model inference
Experience integrating model outputs into product flows (APIs, feature flags) and measuring impact through experiments and product metrics
Experience with model lifecycle and operations: model registries, CI/CD for models, reproducible training, offline & online parity, monitoring and incident response

Job Responsibility

Embed model inference into Network Enablement product flows and decision logic (APIs, feature flags, backend flows)
Define and instrument product + ML success metrics (fraud reduction, retention lift, false positives, downstream impact)
Design and run experiments and rollout plans (backtesting, shadow scoring, A/B tests, feature-flagged releases) to validate product hypotheses
Build and operate offline training pipelines and production batch scoring for bank intelligence products
Ship and maintain online feature serving and low-latency model inference endpoints for real-time partner/bank scoring
Implement model CI/CD, model/version registry, and safe rollout/rollback strategies
Monitor model/data health: drift/regression detection, model-quality dashboards, alerts, and SLOs targeted to partner product needs
Ensure offline and online parity, data lineage, and automated validation / data contracts to reduce regressions
Optimize inference performance and cost for real-time scoring (batching, caching, runtime selection)
Ensure fairness, explainability and PII-aware handling for partner-facing ML features

What we offer

medical
dental
vision
401(k)
equity
commission

Fulltime

Senior Software Engineer – ML Model Compliance & Automation

We are seeking a highly skilled and motivated Senior Software Engineer to lead t...

Location

India , Jaipur

Salary:

Not provided

InfoObjects

Expiration Date

Until further notice

Requirements

Experience Required: 3 - 7 yrs
GoLang (preferred)
Python (preferred)
Bash
MLOps Tools: KitOps, MLModelCI, MLflow, ONNX, TensorFlow, PyTorch, Docker
SBOM & Security: Syft, Grype, Trivy, CycloneDX, SPDX
CI/CD: GitHub Actions, GitLab CI, Jenkins, ArgoCD
Infra: Kubernetes, Docker, Helm, Terraform
Cloud: AWS, GCP, Azure (EKS/GKE/ECS preferred)
Version Control: Git, GitOps

Job Responsibility

Model Packaging & Artifact Management: Design and implement workflows for packaging ML models using KitOps, ONNX, MLflow, or TensorFlow SavedModel
Manage model artifact versioning, registries, and reproducibility
Ensure artifact integrity, consistency, and traceability across CI/CD pipelines
Model Profiling & Optimization: Automate model profiling (latency, size, ops) using MLModelCI, TorchServe, or ONNX Runtime
Apply quantization, pruning, and format conversions (e.g., FP32→INT8) for optimization
Embed profiling and optimization checks into CI/CD pipelines to assess deployment readiness
Compliance & SBOM Generation: Develop pipelines to generate and validate SBOMs for ML models
Implement compliance checks for licensing, vulnerabilities, and security using CycloneDX, SPDX, Syft, or Trivy
Validate schema, dependencies, and runtime environments for production readiness
Cloud Integration & Deployment: Automate model registration, endpoint creation, and monitoring setup in AWS/GCP/Azure

Fulltime

Software Engineer (Data Engineering)

We are seeking a Software Engineer (Data Engineering) who can seamlessly integra...

Location

India , Hyderabad

Salary:

Not provided

NStarX

Expiration Date

Until further notice

Requirements

4+ years in Data Engineering and AI/ML roles
Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field
Python, SQL, Bash, PySpark, Spark SQL, boto3, pandas
Apache Spark on EMR (driver/executor model, sizing, dynamic allocation)
Amazon S3 (Parquet) with lifecycle management to Glacier
AWS Glue Catalog and Crawlers
AWS Step Functions, AWS Lambda, Amazon EventBridge
CloudWatch Logs and Metrics, Kinesis Data Firehose (or Kafka/MSK)
Amazon Redshift and Redshift Spectrum
IAM (least privilege), Secrets Manager, SSM

Job Responsibility

Design, build, and maintain scalable ETL and ELT pipelines for large-scale data processing
Develop and optimize data architectures supporting analytics and ML workflows
Ensure data integrity, security, and compliance with organizational and industry standards
Collaborate with DevOps teams to deploy and monitor data pipelines in production environments
Build predictive and prescriptive models leveraging AI and ML techniques
Develop and deploy machine learning and deep learning models using TensorFlow, PyTorch, or Scikit-learn
Perform feature engineering, statistical analysis, and data preprocessing
Continuously monitor and optimize models for accuracy and scalability
Integrate AI-driven insights into business processes and strategies
Serve as the technical liaison between NStarX and client teams

What we offer

Competitive salary and performance-based incentives
Opportunity to work on cutting-edge AI and ML projects
Exposure to global clients and international project delivery
Continuous learning and professional development opportunities
Competitive base + commission
Fast growth into leadership roles

Fulltime

ML Engineer

The IT company Andersen invites an experienced ML Engineer for a large-scale pro...

Location

Salary:

Not provided

Andersen

Expiration Date

Until further notice

Requirements

Experience as a ML Engineer for 3+ years
Strong proficiency in Python, with deep knowledge of software development principles, architecture patterns, and ML model integration
Hands-on experience with TTS systems (e.g., Tacotron, FastSpeech, VITS) and an understanding of SST pipelines
Familiarity with real-time AI systems, including LLM integration and latency-sensitive applications
Experience tuning and maintaining ML models for performance, scalability, and quality in production
Level of English – from Intermediate+

Job Responsibility

Designing, integrating, and optimizing Text-to-Speech (TTS) systems within real-time conversational AI pipelines
Fine-tuning models based on user feedback, improving clarity, naturalness, and emotional expression in voice output
Contributing to customer-specific deployments with high adaptability and quick turnaround requirements
Collaborating with ML, product, and engineering teams to ensure seamless voice experiences across our platform

What we offer

Experience in teamwork with leaders in FinTech, Healthcare, Retail, Telecom, and others
The opportunity to change the project and/or develop expertise in an interesting business domain
Guarantee of professional, financial, and career growth
The opportunity to earn up to an additional 1,000 EUR per month, depending on the level of expertise, which will be included in the annual bonus, by participating in the company's activities
Access to the corporate training portal
Bright corporate life (parties / pizza days / PlayStation / fruits / coffee / snacks / movies)
Certification compensation (AWS, PMP, etc)
Referral program
English courses
Private health insurance and compensation for sports activities